Data engineering consulting firms

AWS, Azure, GCP, Snowflake, Databricks

Large enterprises running multi-cloud transformations across AWS, Azure, and GCP simultaneously, where a single integrator needs to own the full program.

Weak fit for a focused Snowflake modernization: it is built to own whole multi-cloud programs. phData, a Snowflake Elite partner, is the narrower option.

Snowflake, Databricks, AWS, Azure, GCP

Enterprise data, cloud, and analytics work across financial services, insurance, retail, and other sectors. Ask for references from similar projects.

For a small task, check whether the proposed work and team match what you need. Confirm which regional office will deliver it and ask for written commercial terms. Retail is part of Adastra's published work.

Snowflake, Databricks, AWS, Azure, GCP

Consider Aimpoint for programs using Snowflake, Databricks, and dbt. It lists credentials for all three; ask for relevant references and the names of the proposed consultants.

Ask for the proposed consultants, delivery locations, and a quote before choosing Aimpoint. Its listed credentials and the headcount shown here are unverified, so neither tells you team availability or what your project will cost.

AWS, Azure, GCP

Custom connector development and large-scale data replication

Narrow scope for work beyond ingestion: its listed focus is custom Airbyte connectors and pipelines, and AI/ML enablement is rated Low.

Databricks, Snowflake, AWS, Azure, GCP

Data engineering and analytics; distributed data processing

Look elsewhere if deep single-platform credentials decide the shortlist: its listed focus is distributed processing across clouds. Check any required partner tier.

Snowflake, AWS, Azure, GCP, Databricks

Mid-market companies needing end-to-end data solutions; data modernization projects

Less suited to a buyer who needs depth on one platform: Analytics8 covers the full data lifecycle across Snowflake, Databricks, dbt, and BI tools.

Snowflake, Databricks, AWS

Active data governance and metadata management setup

Weak fit for platform migration or AI/ML engineering: its listed focus is catalog, lineage, and governance setup, and AI/ML is rated Low.

Snowflake, AWS, Azure

Snowflake and Salesforce integration; AI-native consulting

A poor match for a Databricks-first, GCP-native, or non-Salesforce CRM stack: its listed focus is Snowflake and Salesforce. Ask for references on your stack.

AWS, Azure, GCP, Snowflake, Databricks

Regulated industries; nearshore teams; life sciences and finance

Not the right pick for a data-only engagement: Avenga is a broad software and cloud firm. Ask for the proposed data architects and comparable platform projects.

Snowflake, AWS, Azure, GCP

Private equity firms and portfolio companies that need due-diligence analytics strategy on Snowflake. Ask which implementation work Bain will own.

Wrong choice for a hands-on dbt and Snowflake build: Bain leads with strategy and advisory work. Brooklyn Data is the closer fit for that stack.

Databricks, AWS, Azure, GCP

Boards and executive teams commissioning a deep-tech or AI venture build through BCG X. Confirm who owns engineering delivery alongside the strategy work.

Wrong choice for a fixed-scope analytics or ML implementation: BCG X is a venture-build and strategy partner. Compare Tiger Analytics for delivery.

Azure, AWS, Databricks

Microsoft technologies and PowerBI consulting; .NET development

Weak fit for a Snowflake-led program or a Databricks build outside Azure: its listed focus is Microsoft, PowerBI, and .NET. Ask for references on your stack.

Databricks

Open-source big data; Elasticsearch and OpenSearch specialists

Wrong choice for a cloud-managed warehouse migration: its listed focus is Elasticsearch, OpenSearch, and streaming. Ask for target-platform references.

Azure, Databricks, AWS, Snowflake

Asian markets; Microsoft Azure and PowerBI specialists

Poor fit for delivery outside Asia or a Snowflake- or Databricks-led build: its listed focus is Azure and PowerBI for Asian enterprises. Confirm delivery locations.

Databricks, Snowflake, AWS, Azure

Mid-market companies modernizing to a cloud data stack on Databricks or Snowflake with AWS or Azure. Ask for comparable implementations and the proposed team.

Not the pick for GCP delivery or an AI/ML-led program, where it is rated Moderate. Ask for references and named specialists.

Snowflake

Companies building or maturing a dbt-centered data stack with Snowflake, Looker, and Fivetran. Brooklyn Data is now part of Velir; ask for references matched to your scope.

Less suited to Databricks, GCP, or work beyond a dbt-centered analytics stack: its listed focus is dbt with Snowflake, Looker, and Fivetran.

AWS, Azure, GCP, Snowflake, Databricks

European industrial and engineering-intensive enterprises running Industry 4.0 or R&D data programs where manufacturing-domain depth and on-continent delivery are requirements.

Overbuilt for a focused Databricks MLOps program: it targets large European industrial programs. Datapao is the narrower Databricks option.

Azure, Databricks, Snowflake, AWS, GCP

Microsoft Azure specialists; PowerBI and AI solutions

Weak fit for an AWS- or GCP-led program: its listed focus is Azure, PowerBI, and Azure AI. Ask for consultants on the target cloud.

Azure, AWS, GCP, Databricks

AI-driven software development; GenAI integration; healthcare tech

Wrong choice for a migration-led program: its listed focus is GenAI and AI-driven software, and platform migration is rated Moderate.

AWS, Azure, GCP, Snowflake, Databricks

Large retailers and consumer-goods companies running GenAI modernization programs that need a large delivery bench and long-standing enterprise relationships.

Overkill for a focused retail or CPG analytics program. Ask for the proposed team and a scoped quote; Tredence is the analytics-focused alternative.

AWS, Azure, GCP

Enterprise-scale event streaming and data in motion

Poor fit for a batch warehouse build, BI, or AI/ML beyond Kafka: its listed focus is real-time event streaming, and AI/ML and analytics are rated Moderate.

Snowflake

Financial-services data cloud work on Snowflake, FactSet, or SimCorp. Confirm any required Snowflake partner tier.

Wrong choice outside financial services: its listed focus is FactSet, SimCorp, and Snowflake. For retail, healthcare, or manufacturing, ask for sector references.

AWS, Snowflake

Modern data orchestration and data platform engineering context

Skip it if your orchestrator is not Dagster or you want one supplier for the whole stack: its listed focus is Dagster orchestration.

AWS, Azure, GCP, Databricks, Snowflake

Enterprise data modernization; Big Data solutions

Weak fit if a specific Snowflake or Databricks partner tier is required: its listed strength is broad multi-cloud coverage. Verify any tier with the platform.

Snowflake, Databricks, AWS

Modern data stack implementation and analytics engineering

Poor fit for platforms outside Snowflake, Databricks, AWS, and dbt: it is a boutique built around that stack. Confirm the named team for parallel workstreams.

AWS, Azure, GCP, Databricks, Snowflake

Custom software development with data engineering; European nearshore

Less suited to a buyer who needs deep single-platform specialization: DataArt is built for custom software and data work across all clouds.

Snowflake

dbt implementation and analytics engineering workflow optimization

Wrong choice for AI/ML engineering or work beyond dbt and Airflow: its listed focus is analytics engineering, and AI/ML is rated Low.

Snowflake, AWS, Azure

Data governance and managed data services

Weak fit if your integration layer is not Talend or your warehouse is not Snowflake, or if you need local delivery outside the UK. Confirm locations and staffing.

Databricks, Azure, AWS

European companies running Databricks on Azure or AWS that need MLOps and Spark/Kafka expertise. Confirm current credentials and the proposed consultants.

Not the right pick for a Snowflake-led program or local delivery outside Europe: its listed focus is Databricks, MLOps, and Spark. Confirm delivery locations.

AWS, Azure

AI-driven data engineering and MLOps implementation

Poor fit for Snowflake, GCP, or BI-led work: its listed focus is MLOps and AI-driven data engineering, with business analytics rated Moderate.

Databricks, AWS, Azure, GCP

Teams building or scaling a Databricks or MLflow-based ML platform on AWS, Azure, or GCP. Ask for matching project references and named specialists.

A Snowflake-centric warehouse is outside its listed stack of Databricks, Spark, and MLflow. For a large multi-cloud program, ask for named specialists per cloud.

Snowflake, Databricks, AWS, GCP

Teams migrating existing analytics code to dbt, standardizing dbt practices, or training analytics engineers with the creators of dbt. Confirm the proposed instructors.

Not the partner for end-to-end platform delivery: its services scope is dbt and analytics engineering. For ingestion or orchestration, plan on another provider.

AWS, Azure, GCP, Snowflake, Databricks

Regulated-industry enterprises (healthcare systems, banks, insurers) that need C-suite advisory, compliance framing, and Big Four sign-off alongside the technical delivery.

Weak fit for a mid-market Snowflake migration in healthcare or financial services that needs no Big Four advisory. Compare Hakkoda, or ask for engineering quoted apart.

AWS, GCP, Azure, Snowflake, Databricks

European enterprises; cloud and cybersecurity specialists

Weak fit if you need local delivery outside Europe: it is positioned as a European consultancy. For a small engagement, ask for a scoped team and quote.

Azure, GCP, AWS, Databricks

AI and data analytics for global brands; GenAI solutions

Snowflake is not in its listed stack, so a Snowflake-first warehouse or older-system migration is a stretch next to its Azure, GCP, Databricks, and MLOps focus.

Azure, Databricks

Microsoft stack optimization and Power BI enterprise rollouts

Choose elsewhere for an AWS- or GCP-led program: its listed stack is Azure, Power BI, and Databricks. Ask for target-cloud references if you still consider it.

AWS, Azure, GCP, Snowflake, Databricks

End-to-end data engineering; data lakehouse implementations

Weak fit for mainframe, SAP, or older on-premises integrations: its listed focus is lakehouses and streaming. Ask for references on those systems.

Azure, Snowflake, Databricks

Global compliance, audit-ready data platforms, and finance transformation

Overbuilt for a straightforward data migration that needs no audit, compliance, or finance-data depth. Ask EY to scope technical delivery apart from advisory work.

Snowflake, Databricks, AWS, GCP

Fivetran implementation, connector work, and assisted transformations, including data modeling, SQL, and dbt.

For work beyond the Fivetran services package, agree on who will deliver analytics and AI tasks. Fivetran explicitly offers transformation and modeling work; the proposal needs to define the rest of the program.

AWS, Azure, GCP, Snowflake, Databricks

Enterprise AI and decision intelligence for large enterprises

Not the pick when platform depth is the main criterion: its listed focus is decision intelligence and analytics. For a platform migration, ask for target-platform references.

Snowflake, AWS, Azure

Healthcare and financial-services teams building Snowflake data platforms where compliance experience matters. Ask for references that match your requirements.

A BigQuery- or Databricks-led roadmap sits outside its listed Snowflake focus (plus AWS, Azure, dbt). For a multi-year program, confirm staffing commitments.

Snowflake, Azure, AWS, Databricks

Enterprises needing cloud migrations and IoT data solutions

GCP is not in its listed stack of Snowflake, Azure, AWS, Databricks, and dbt, so a GCP-led program is a weak fit. For a large contract, confirm staffing with NTT DATA.

GCP, AWS, Azure, Snowflake

Large-scale migrations off older systems and managed services outsourcing

Built for scale, so a small migration or short implementation may feel oversized. Ask HCLTech for a right-sized team and quote.

AWS, Azure, Databricks

Open-source BI, data warehousing, and analytics implementations. Ask for references with the tools you use.

Weak fit for a complex cloud migration or AI/ML program: its listed focus is open-source BI and data warehousing. Ask for comparable projects first.

Snowflake, GCP

Reverse ETL and Data Activation strategy

Not a general data engineering partner: its listed focus is Reverse ETL and data activation. For warehouse builds, migrations, or ML work, ask who delivers it.

Azure, AWS, Databricks, Snowflake

Software consultancy with data engineering; Agile delivery

Poor match when a specific platform partner tier is mandatory or the program is AI/ML-led: it is a software consultancy first. Verify tiers with the provider.

AWS, Azure, GCP, Databricks

AI/ML and data science projects; predictive analytics

Not built for warehouse or platform migration: its listed focus is AI and data science. Ask for source-to-target references and cutover experience.

Azure, Databricks, AWS, GCP, Snowflake

Product engineering with data modernization; Digital assurance

Snowflake-first engagements are a weaker fit: its listed accelerator targets Databricks. If a Snowflake partner tier is mandatory, verify it with Snowflake.

Snowflake, AWS

Data teams adopting Data Vault methodology on Snowflake with dbt. Ask for Data Vault 2.0 references and the proposed consultants.

Its listed stack is Snowflake, dbt, and AWS, so a Databricks- or GCP-led program, or one firm owning a multi-platform estate, is a weak fit.

Databricks, AWS, Azure, GCP, Snowflake

Global enterprises; offshore development model; large-scale implementations

Likely oversized for a small or time-sensitive implementation: it is a massive global delivery organization. Ask for a scoped team, approval path, and quote.

AWS, Azure, GCP, Databricks

Full-cycle software development with data engineering; Eastern Europe

If delivery must be domestic or on-site outside Eastern Europe, or Snowflake or dbt credentials are required, this is a weak fit. Ask for locations and matching references.

AWS, Azure, GCP, Databricks, Snowflake

Automotive, fintech, and large-scale engineering projects

Healthcare, retail, or logistics work needing sector-specific depth is a weak fit: its listed industries center on automotive, financial services, and insurance.

Snowflake, AWS, Azure, GCP

BI and analytics deployments; Tableau and Snowflake specialists

Weak fit for a Databricks-led or ML engineering program: its listed focus is Snowflake, Tableau, and Matillion analytics. Ask for comparable projects and named specialists.

AWS, Azure, GCP, Databricks

VC-backed startups and rapidly scaling tech firms

A Snowflake-specific engagement is a weak fit: Snowflake is not in its listed stack. If a partner tier is required, verify it with the platform provider.

AWS, Azure, GCP, Snowflake, Databricks

Mid-market companies; full-cycle software development with data engineering

Weak fit for a data-only engagement: it is a full-cycle software developer with analytics alongside. Ask for the proposed data architects and platform references.

Azure, AWS, GCP, Databricks, Snowflake

Intelligent automation and data analytics; Microsoft Azure specialists

Snowflake-led programs outside Azure are a weak fit: its listed stack leads with Azure and Power BI. Ask for Snowflake references and the proposed architects.

Azure, Snowflake, AWS

Risk management, regulatory reporting, and finance back-office data

Not the first pick for AI/ML engineering: its listed focus is governance, compliance, and finance data. Ask for named practitioners and delivery references.

Snowflake, Databricks, AWS, Azure

Companies seeking Snowflake-to-Databricks migration; cloud data platform specialists

A GCP, BigQuery, or AI/ML-led program is a weak fit: its listed focus is Snowflake-to-Databricks migration. For parallel workstreams, confirm staffing.

Snowflake, Azure, AWS, Databricks

Snowflake migrations for large enterprises

A small scope or non-Snowflake target is a weak fit: its profile centers on Snowflake, though Azure, AWS, and Databricks are listed. Ask for a scoped team and quote.

Databricks, Snowflake, AWS, Azure, GCP

Australia and New Zealand enterprises considering Databricks or Snowflake work, including regulated-industry programs. Verify required partner credentials and domain references.

Not the pick if you need on-site delivery outside Australia and New Zealand, where Mantel Group focuses. Confirm its delivery locations first.

AWS

Consider Materialize for operational dashboards and real-time analytics using streaming SQL with Kafka and PostgreSQL. Confirm that its services cover your data sources and latency requirements.

Weak fit for a batch Snowflake or Databricks warehouse migration: its listed focus is streaming SQL and real-time data products.

Snowflake, AWS, Azure, GCP

Large-scale digital transformation and strategy-led AI initiatives

Poor match for a scoped, hands-on cloud data migration: its QuantumBlack work is strategy-led. Ask which team would do the implementation.

Snowflake, Databricks

Implementing data observability and data reliability engineering

Not a general data engineering partner: its listed focus is data observability and reliability, so migration or AI/ML builds sit outside its core scope.

AWS, Azure, Snowflake

Banking and capital-markets firms running structured data modernization programs on Snowflake where financial-services domain expertise is a baseline requirement.

Heavier than needed for a focused Snowflake Data Vault build: it is positioned for banking modernization programs. Compare Infostrux, a pure-play Snowflake partner.

AWS, Azure, GCP, Snowflake, Databricks

European nearshore development; enterprise clients

A mismatch if US-domestic or on-site delivery is mandatory: its listed focus is European nearshore. Confirm consultant locations and staffing terms.

Snowflake, GCP

Analytics engineering productivity tools and consulting

Weak fit for Databricks, infrastructure, or AI/ML engineering work: its listed focus is dbt analytics engineering on Snowflake and BigQuery.

AWS, Azure, GCP, Snowflake, Databricks

Digital transformation; enterprise data and analytics

A generalist for broad digital programs, not a single-platform specialist: its listed stack runs from AWS and Snowflake to Salesforce and Adobe.

Snowflake, AWS, Databricks

Consider phData for Snowflake data engineering, migrations, and SAP-to-Snowflake analytics. Snowflake confirms its Elite tier; check references for your source systems and agree on the work before hiring.

For broad ERP implementation or work across several target platforms, ask for references covering those tasks. phData's SAP page describes analytics, not ERP or mainframe delivery.

AWS, Azure, Databricks

Data engineering and analytics for startups and mid-market

Look elsewhere for a Snowflake- or GCP-led migration: neither is in its listed stack of AWS, Azure, Databricks, Spark, Kafka, and Airflow.

Azure, AWS, GCP, Snowflake, Databricks

Data consultancy and bioinformatics; enterprise data mesh

Less suited to a large multi-workstream program: its listed focus is bioinformatics and data consultancy. Ask for named leads and staffing commitments.

Azure, AWS, GCP, Snowflake

Busines-led transformation and finance function modernization

Poor fit for a focused, engineering-led pipeline build: its listed focus is business-led transformation. Ask PwC to scope engineering deliverables separately.

Snowflake, Databricks, GCP

Warehouse-native Customer Data Platform (CDP) implementation

Scope ends at customer data: its listed focus is warehouse-native CDP implementation, not batch migration, AI/ML, or cross-cloud modernization.

Azure, Databricks, AWS

Microsoft Azure specialists; Industrial IoT and smart machines

Weak fit for a Snowflake, Google Cloud, or non-industrial program: its listed focus is Azure, Databricks, and industrial IoT.

AWS, Azure, GCP, Databricks, Snowflake

Healthcare and financial services; compliance-focused data solutions

Not the choice if a platform-specific specialist is required: its coverage is broad. Verify any mandatory Snowflake or Databricks partner tier with the vendor.

Snowflake, Databricks, AWS, GCP, Azure

Consider Sigmoid for ML engineering and data platform work across Snowflake, Databricks, and the major clouds. Confirm target-platform references and a current quote.

Wrong choice for a regulated-industry program that hinges on deep compliance expertise: its listed focus is ML engineering breadth across platforms.

AWS, Azure, GCP, Databricks, Snowflake

Consider Simform when application development and cloud data infrastructure need to be delivered together across AWS, Azure, GCP, Databricks, and Snowflake. Confirm workstream ownership.

A product-engineering shop first, so a weak match for a standalone warehouse migration. Ask for data-only migration references.

AWS, Azure, GCP, Snowflake, Databricks

Consider Slalom for enterprise digital transformation, including AWS and GenAI programs. Ask for comparable implementations and the proposed cloud and data engineering team.

Overbuilt for a focused Snowflake, Databricks, and dbt engagement: it is positioned for enterprise transformation. Compare Aimpoint Digital, which lists all three.

Snowflake, AWS, Azure, GCP, Databricks

Nordic organizations considering Snowflake or broader data transformation. Verify required partner credentials and request references for the target platforms.

Weak fit for local delivery outside Europe or an AWS- or Databricks-led program: its listed focus is Nordic organizations and Snowflake.

Snowflake, Databricks, AWS, Azure, GCP

European nearshore data engineering for fintech, manufacturing, or logistics. Ask for relevant project references and verify any required AWS or Snowflake credentials.

Limited for programs needing local delivery in several regions: its listed focus is European nearshore. Ask for delivery locations and named consultants.

AWS, Azure, GCP, Databricks, Snowflake

Multinational enterprises considering multi-year data platform transformation with an offshore delivery component. Confirm regional coverage and staffing commitments in the proposal.

Too large-scale for a focused mid-market ML or analytics build: TCS targets multi-year multinational programs. Compare Sigmoid for focused ML engineering.

AWS, Azure, GCP

Telecom operators and large manufacturers running multi-year data platform programs where offshore delivery economics and domain-specific process knowledge are primary selection criteria.

Overkill for a mid-market dbt and Snowflake build: its listed focus is multi-year telecom and manufacturing programs. Compare Bluecloud for the modern data stack.

AWS, Azure, GCP, Databricks, Snowflake

Organizations adopting data mesh and modern data architecture. Ask Thoughtworks for comparable implementations and a delivery plan suited to the organization's operating model.

More than a focused dbt implementation or training engagement needs: it is positioned for data mesh. Compare dbt Labs Services, which lists dbt implementation and training.

Snowflake, Databricks, AWS, GCP, Azure

Consider Tiger Analytics for retail and CPG analytics, AI/ML, and GenAI programs. Ask for relevant implementations and named specialists.

Weak fit when a platform-led migration is the core need: its listed focus is analytics, AI/ML, and GenAI. Ask for named engineers and target-platform references.

Snowflake, Databricks, AWS, Azure, GCP

Consider Tredence for retail and CPG analytics or GenAI programs. Request comparable implementations and evidence for any accelerator savings it cites.

Weak fit for a small delivery pod or a platform-specific migration: its listed focus is retail and CPG analytics and GenAI. Ask for the proposed team.

AWS, Azure, GCP, Snowflake, Databricks

Large-scale global enterprises; offshore delivery model

Wrong scale for a focused mid-market implementation: Wipro is positioned for large global enterprises on an offshore model. Ask for a scoped team and quote.

AWS, Azure, GCP, Databricks

Agentic AI systems; real-time analytics; platform engineering

Wrong choice for a batch warehouse or Snowflake-led migration: Snowflake is absent from its listed stack, which centers on agentic AI and streaming.