Senior Technical Delivery Manager - Data Platforms

Employment: Contract Experience: Mid-Senior level Exerizon is a fast-growing strategy and technology consulting firm founded by former senior leaders from global consulting and cloud organizations. We help current and future market leaders tackle their greatest challenges — from digital strategy and cloud transformation to data & AI platforms and application modernization. We redefined the traditional consulting model: we share risk with our clients through impact-based remuneration, and we share ownership with our people from day one. We are looking for a Senior Technical Delivery Manager to lead data platform programmes for our clients — lakehouse and warehouse builds, migrations and modernisation on Databricks and Snowflake . This is a technical leadership role, not a pure PMO seat: you own scope, plan, budget, quality and the client relationship, and you understand the architecture, the pipelines and the cost model well enough to challenge both the team and the client. What you will do: Lead end-to-end delivery of data platform engagements — mobilisation, discovery, build, migration, go-live and hypercare — on Databricks and Snowflake, typically on Azure or AWS Own the delivery plan, scope, budget, staffing and risk register; run steering committees and report to client executives with no surprises Shape and defend the technical approach with the lead architect: lakehouse (medallion) vs. warehouse-centric design, ingestion patterns (batch, CDC, streaming), transformation (dbt, Delta Live Tables), orchestration (Databricks Workflows, Azure Data Factory, Airflow), data quality and observability Run the engineering cadence: backlog, sprint planning, release management, environment strategy and CI/CD discipline (Git, Databricks Asset Bundles, Terraform, Snowflake schema change management), definition of done Manage migration workstreams from legacy platforms (Oracle, Teradata, SQL Server, on-prem Hadoop) to cloud: data reconciliation, cut-over planning, parallel run, decommissioning Keep platform economics under control: DBU and Snowflake credit consumption, warehouse and cluster sizing, cluster policies, FinOps reporting to the client Build governance in from the start: Unity Catalog / Snowflake Horizon, access models, PII handling, lineage and audit — to the standard regulated clients (banking, insurance, healthcare) expect Lead mixed teams of 5–15 data engineers, architects, analysts and QA drawn from Exerizon, the client and vendors; coach and grow them Contribute to Exerizon's growth: proposals and estimates, delivery methods and accelerators, pre-sales support Requirements 8+ years in data and analytics delivery, including 3+ years as a delivery, project or engagement manager accountable for programme outcomes (scope, budget, timeline, quality) At least two production data platform programmes delivered end to end on Databricks and/or Snowflake — greenfield build or migration — with hands-on knowledge of what breaks at go-live Technical fluency, not just vocabulary: you read SQL and PySpark, understand Delta Lake and Iceberg table formats, Unity Catalog, Snowflake virtual warehouses, streams and tasks, and Snowpark; you can review a pipeline design and challenge an estimate Solid delivery management toolkit: estimation, scope and change control, budget and estimate-at-completion tracking, risk and issue management, vendor and SI coordination, agile and hybrid delivery models Cloud literacy on Azure or AWS at the solution level: networking, identity, storage, cost Experience delivering in regulated industries (banking, insurance, healthcare) with data governance, privacy (GDPR) and audit requirements built into the delivery Executive-level communication: structured written status, clean steering decks, and the habit of raising bad news early with options attached Full professional fluency in Polish and English Nice to have: Databricks (Certified Data Engineer / Platform Architect) or Snowflake (SnowPro Core / Advanced) certifications PMP, PRINCE2 or SAFe certification dbt, Terraform, Microsoft Fabric or Azure Synapse exposure Delivery of ML/AI workloads on the platform (MLflow, feature stores, model serving) Data mesh or domain-oriented data ownership in practice Benefits Full ownership of your engagements and direct access to client executives — no ten-layer review pyramid Competitive compensation on B2B contract Annual training and certification budget, including Databricks and Snowflake certification tracks Remote work model with access to a central Warsaw office A seat at the table in shaping a young firm: our data & AI offering, delivery methods, hiring and culture