14 providers · Sweden
Data Engineering and Analytics Providers in Sweden
The data engineering and analytics market in Sweden serves the country's banking and telecommunications and equipment sectors as well as the broader enterprise IT estate concentrated in Stockholm. Data engineering and analytics providers build the pipelines, warehouses, lakehouses and BI layers that let enterprises move from operational data to decisions. Work spans Snowflake, Databricks, BigQuery and Synapse delivery, real-time streaming, semantic-layer design, and embedded analytics in operational products. TechVendorIndex tracks 14 providers actively delivering data engineering and analytics engagements in Sweden, drawn from global systems integrators, regional champions and specialist boutiques.
About data engineering and analytics in Sweden
Data pipelines, warehousing, bi and analytics consulting. Buyers in Sweden typically engage providers in this category to support transformation work tied to banking and telecommunications and equipment priorities, with delivery shaped by local obligations under EU GDPR, the Swedish Protective Security Act, the Finansinspektionen outsourcing rules and the MSB cyber guidance.
Top data engineering and analytics providers in Sweden
The 14 firms below are ranked by verified delivery presence in Sweden, with focus and rating drawn from TechVendorIndex verified reviews. No vendor pays for placement.
Provider
Focus in Data Engineering and Analytics
Rating
Reviews
Accenture Sweden
HQ: Stockholm · BFSI, telecom, public sector
Data pipelines, lakehouse and BI
4.2
520 reviews
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Capgemini Sweden
HQ: Stockholm · SAP, engineering, public sector
Data pipelines, lakehouse and BI
4.0
460 reviews
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Tietoevry
HQ: Stockholm · Banking, public sector, managed
Data pipelines, lakehouse and BI
4.0
720 reviews
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CGI Sweden
HQ: Stockholm · Public sector and BFSI
Data pipelines, lakehouse and BI
4.0
540 reviews
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Knowit
HQ: Stockholm · Digital and design
Data pipelines, lakehouse and BI
4.2
380 reviews
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Sopra Steria Sweden
HQ: Stockholm · Public sector and integration
Data pipelines, lakehouse and BI
4.0
240 reviews
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HiQ
HQ: Stockholm · Custom development
Data pipelines, lakehouse and BI
4.1
260 reviews
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Cygate (Telia)
HQ: Stockholm · Network and security
Data pipelines, lakehouse and BI
3.9
220 reviews
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Atea Sweden
HQ: Stockholm · Infrastructure and reseller
Data pipelines, lakehouse and BI
4.0
320 reviews
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Sigma IT
HQ: Gothenburg · Custom development and SAP
Data pipelines, lakehouse and BI
4.1
260 reviews
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Deloitte Sweden
HQ: Stockholm · ERP, cyber, advisory
Data pipelines, lakehouse and BI
4.2
380 reviews
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TCS Sweden
HQ: Stockholm · BFSI and application services
Data pipelines, lakehouse and BI
4.0
320 reviews
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Infosys Sweden
HQ: Stockholm · BFSI and application services
Data pipelines, lakehouse and BI
4.0
280 reviews
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Cognizant Sweden
HQ: Stockholm · BFSI application services
Data pipelines, lakehouse and BI
3.9
260 reviews
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Data Engineering and Analytics market overview in Sweden
Within the broader SEK 230 billion enterprise IT services market in Sweden, data engineering and analytics is one of the more active disciplines, growing roughly in line with the 4.1% headline expansion of the wider services market. Demand is concentrated in Stockholm and Gothenburg, where the largest banking and telecommunications and equipment buyers maintain dedicated programme teams. Procurement decisions are shaped by the fact that Sweden is a small market with outsized R&D intensity, anchored by Ericsson, Volvo, the major Nordic banks and a strong gaming and fintech base in Stockholm. Data platforms in Sweden are consolidating around lakehouse architectures (Databricks and Snowflake) with reverse-ETL into operational systems. AI workloads have made data quality and lineage governance the primary investment focus rather than reporting BI. Mid-market buyers in Sweden increasingly favour specialist firms with deep domain expertise over generalist consultancies, while the largest programmes continue to be awarded to the multinational integrators with global delivery models and embedded banking practices.
How to select a data engineering and analytics provider in Sweden
Use the following criteria to shortlist providers before issuing a formal request for proposal. Most procurement teams in Sweden weight references and operating-model fit more heavily than headline rate cards.
- Lakehouse or warehouse platform certifications appropriate to the buyer's stack
- Data product thinking and clear ownership models for produced datasets
- Reference implementations at comparable data volume in banking
- Strong opinion on data quality, observability and lineage tooling
- Capability to deliver streaming and batch in the same engagement
Typical engagement model
Platform foundation work typically runs three to six months at USD 500,000 to USD 2M. Steady-state data engineering pods cost USD 35,000 to USD 80,000 per month depending on seniority and location. Major migrations from legacy warehouses (Teradata, Netezza) extend to 12 to 18 months.
Pricing should always be benchmarked against at least three references in Sweden at comparable scope. Engage independent advisory support before signing multi-year contracts above USD 5M annual contract value.
Related categories and regions
Compare the data engineering and analytics market in Sweden with other service lines in the same country, or with data engineering and analytics in other markets covered by TechVendorIndex.
Frequently asked questions
Snowflake or Databricks in Sweden?
Snowflake is most often selected by buyers prioritising SQL workloads and data sharing with partners. Databricks is selected when machine-learning and data engineering converge on the same platform. Many enterprises in Sweden run both.
How do we improve data quality in Sweden?
Establish data product ownership at the source-system level, deploy automated quality monitoring, define SLAs for produced datasets, and treat data contracts between teams as first-class artefacts. Tooling alone does not solve organisational gaps.
Is generative AI changing data engineering priorities in Sweden?
Yes — RAG and agent workloads have raised the cost of poor data lineage and made unstructured-data pipelines a first-class concern. Buyers in Sweden are increasingly investing in vector search and document chunking pipelines.
How do we measure the ROI of a data programme in Sweden?
Tie every data product to a named business decision or operational process, track decision quality and cycle time rather than dashboard adoption, and review the data product portfolio annually against business outcomes.
Last updated: May 2026