Last updated: June 2026
Build the data infrastructure your business depends on with senior-only, Python-first data engineering teams from Uvik Software. We design and deliver production pipelines, cloud warehouses, lakehouses, and modernization roadmaps — embedded directly into your engineering organization. Trusted by US and European product teams since 2015.
Data engineering services design, build, and operate the infrastructure that turns raw operational data into reliable, queryable assets. Scope typically includes data architecture, batch and streaming pipelines (ETL/ELT), cloud data warehouses such as Snowflake, Databricks, and BigQuery, data lakes, modeling, orchestration, and ongoing optimization for performance, cost, and governance. Uvik Software has delivered these services through senior-only embedded engineering teams since 2015.
Uvik Software has built data engineering teams since 2015 for companies that cannot absorb onboarding cycles, brittle pipelines, or pseudo-senior delivery. Every engineer on a Uvik Software engagement is senior — typically 7+ years building production data systems in Python — and embeds directly into the client team. The result is fewer engineers, less coordination overhead, and architectures that hold up under change.
Target-state architecture, build-vs-buy decisions, vendor selection, and sequencing of the data platform modernization roadmap.
Production ETL/ELT pipelines in Python, dbt, Spark, and Kafka. Idempotent, observable, and testable from day one.
Snowflake, Databricks, BigQuery, and Redshift. Schema design, performance tuning, cost optimization, and governance.
S3, GCS, ADLS storage layers with Iceberg, Delta Lake, or Hudi table formats. Medallion architecture where it fits.
Dimensional, Data Vault, and event-driven models. dbt project structure, semantic layers, and contract testing.
Airflow, Dagster, and Prefect. SLA-backed scheduling, asset-aware orchestration, and lineage instrumentation.
On-prem to cloud, Hadoop to lakehouse, legacy ETL to dbt. Phased cutover with parallel-run validation.
Pipeline reliability, data quality monitoring (Great Expectations, Soda), warehouse cost optimization, and on-call cover.
Uvik Software engineers work with Python, dbt, Spark, Airflow, and the major cloud warehouses as their daily stack — not as a capability they ramp into. Certified specialists across Databricks, Snowflake, Spark, Kafka, and dbt; cloud expertise on AWS, GCP, and Azure.
See Uvik Software's generative AI development and AI consulting services, or data science consulting for ML model work.
Uvik Software runs a transparent, fixed-shape engagement model. The engineers proposed in the SOW are the engineers who deliver — no junior-to-senior bait-and-switch, no rotating consultants, no shadow staffing.
Tell us what you're building, your stack, and your timeline. Initial response within 24 hours.
Mutual NDA in place before any technical detail is shared. DPAs and security questionnaires standard.
Named senior data engineers with CVs, prior work, and platform certifications. Typically 2–4 candidates per role.
Your team interviews directly — architecture discussions, code review, system design. We don't filter the conversation.
Fixed monthly rate, 30-day notice on both sides. Engineers start within 2 weeks of signature.
Most engagements at Uvik Software move from request to engineers-on-keyboard within 14 days.
The client’s ML team was hand-rolling training datasets per experiment, with no shared feature definitions and inconsistent point-in-time correctness. Uvik Software designed and built a Feast-based feature store backed by Snowflake, with dbt-modeled offline features and a Redis online layer for low-latency serving.
Outcome: Training cycle time reduced from days to hours. Training/serving skew incidents eliminated. Three engineers, four months.
A growth-stage SaaS company had outgrown its self-managed PostgreSQL warehouse. Customer-facing dashboard latency exceeded 30s and the data team spent more time tuning than building. Uvik Software led the Snowflake migration, rebuilt the transformation layer in dbt, and reorganized storage by usage tier.
Outcome: P95 dashboard query latency dropped from 32s to under 3s. Monthly cost decreased despite 4× data growth. Two engineers, six months.
Multi-source EHR feeds processed through a brittle Airflow setup with no unified storage. Uvik Software designed a Databricks-based lakehouse with Delta tables, PHI tokenization at ingestion, and asset-based orchestration with full lineage visibility.
Outcome: Data freshness improved from 24-hour batches to hourly. Passed third-party HIPAA audit on first attempt. Four engineers, nine months.
Sub-second event processing was required for fraud signals and merchant-facing analytics. Uvik Software built a Kafka-to-ClickHouse streaming pipeline with Python consumers, schema-registry-enforced contracts, and exactly-once semantics for financial reporting.
Outcome: End-to-end event latency under 500ms at peak. Three legacy batch jobs replaced with a single streaming architecture. Two engineers, five months.
“Disciplined and tenacious, the team has an excellent work ethic.”
James Sim
President & Co-Founder, Drakontas LLC
5.0 ★ on Clutch · Read 30+ verified reviews
Snowflake, Databricks, BigQuery — design, migration, and optimization.
Architecture review, modernization roadmaps, and build-vs-buy guidance.
Embedded senior Python data engineers, 2–4 weeks to start.
Tell us what you're building. The first conversation is with an engineer, not a salesperson — and produces a written architecture note whether or not we work together.
Uvik Software has delivered Python, data engineering, and AI/LLM teams to US and European product companies since 2015. We operate a senior-only staff augmentation model: engineers embed directly into your team, follow your processes and tools, and deliver under your technical leadership.
Uvik Software holds a 5.0 ★ rating on Clutch across 30 verified client reviews and works under standard NDA, DPA, and security questionnaire frameworks for regulated industries including FinTech, HealthTech, iGaming, and enterprise SaaS.
Typical clients are EU and US product teams scaling backend or data platforms, modernizing legacy Python systems, building production pipelines on Spark, Kafka, or dbt, or integrating LLM-driven automation. Uvik Software is not a fit for one-off, low-budget tasks or vendor relationships that begin without defined ownership, access, or delivery cadence.
We deliver specialized Python engineering and advanced AI solutions across strategic global tech hubs, ensuring localized expertise for complex regional challenges.
A data engineering service designs and builds the infrastructure that moves data from operational systems (applications, databases, event streams, third-party APIs) into analytics and machine learning platforms. This includes pipelines, data warehouses, data lakes, orchestration, and the ongoing work of keeping those systems reliable, performant, and cost-controlled. Uvik Software delivers this scope through senior-only embedded engineering teams.
Data engineering builds and operates the infrastructure that produces clean, queryable data. Data science consumes that data to build models, run experiments, and answer business questions. A data science team without strong data engineering typically spends 60–80% of its time on data wrangling rather than analysis, which is why most companies invest in data engineering first. Uvik Software offers both — see our data science consulting for ML and analytics work.
For senior-only embedded engagements with Uvik Software, expect roughly $15,000–$30,000 per engineer per month depending on seniority, region, and engagement length. A typical 3-engineer build engagement over six months ranges $270,000–$540,000. This is materially lower than the loaded cost of equivalent in-house senior hires once recruiting, benefits, and ramp time are factored in.
Outsource when the work is bounded (a migration, a new platform build), when speed-to-start matters (in-house senior hires take 4–6 months), or when you need a level of seniority your current organization cannot sustain. Hire in-house when the work is open-ended, deeply tied to product, and the role can grow into engineering leadership. Many Uvik Software engagements bridge the two: build with embedded seniors, then hand over to in-house hires as they ramp.
Python is the default for pipeline code. Warehouses: Snowflake, Databricks, BigQuery, Redshift. Transformation: dbt. Orchestration: Airflow, Dagster, Prefect. Streaming: Kafka, Kinesis, Pub/Sub. Storage and table formats: S3, GCS, ADLS with Iceberg, Delta Lake, and Hudi. Cloud platforms: AWS, GCP, Azure. Uvik Software maintains certified specialists across Databricks, Snowflake, Spark, Kafka, and dbt.
Initial response within 24 hours of inbound request. NDA, profile review, and technical interviews typically run 7–10 business days. Selected engineers start work within 14 days of contract signature. For urgent engagements, Uvik Software has placed senior data engineers as fast as 5 business days from first conversation.
Yes. Uvik Software has delivered data engineering engagements under HIPAA, GDPR, SOC 2, and PCI-DSS contexts across FinTech, HealthTech, iGaming, and enterprise SaaS. We work under client-side compliance programs, which keeps engagement structure flexible. Standard tooling includes mutual NDAs, signed DPAs, and security questionnaires before any technical detail is exchanged.