Senior Technical Delivery Manager - Data Platforms

• 8+ years in data and analytics delivery, including 3+ years as a delivery, project or engagement manager accountable for programme outcomes across scope, budget, timeline and quality.
• At least two production data platform programmes delivered end to end on Databricks and/or Snowflake, through greenfield build or migration, with hands-on knowledge of go-live issues.
• Technical fluency: read SQL and PySpark; understand Delta Lake and Iceberg table formats, Unity Catalog, Snowflake virtual warehouses, streams and tasks, and Snowpark; review pipeline designs and challenge estimates.
• Delivery management toolkit covering estimation, scope and change control, budget and estimate-at-completion tracking, risk and issue management, vendor and SI coordination, and agile and hybrid delivery models.
• Cloud literacy at the solution level on Azure or AWS, including networking, identity, storage and cost.
• Experience delivering in regulated industries (banking, insurance, healthcare), with data governance, privacy (GDPR) and audit requirements built into delivery.
• Executive-level communication, including structured written status, steering decks, and raising bad news early with options.
• 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.
• Exposure to dbt, Terraform, Microsoft Fabric or Azure Synapse.
• Delivery of ML/AI workloads on the platform, including MLflow, feature stores and model serving.
• Practical experience with data mesh or domain-oriented data ownership.

• Lead end-to-end delivery of data platform engagements, from mobilisation and discovery through 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.
• Shape and defend the technical approach with the lead architect, covering lakehouse versus warehouse-centric design, ingestion patterns (batch, CDC, streaming), transformation with dbt and Delta Live Tables, orchestration with Databricks Workflows, Azure Data Factory and Airflow, data quality and observability.
• Run the engineering cadence, including backlog, sprint planning, release management, environment strategy, CI/CD discipline using Git, Databricks Asset Bundles, Terraform and Snowflake schema change management, and definition of done.
• Manage migration workstreams from legacy platforms including Oracle, Teradata, SQL Server and on-premises Hadoop to cloud, covering data reconciliation, cut-over planning, parallel run and decommissioning.
• Control platform economics, including DBU and Snowflake credit consumption, warehouse and cluster sizing, cluster policies and FinOps reporting to the client.
• Build governance from the start, covering Unity Catalog / Snowflake Horizon, access models, PII handling, lineage and audit.
• Lead mixed teams of 5–15 data engineers, architects, analysts and QA from Exerizon, the client and vendors; coach and grow them.
• Contribute to Exerizon’s growth through proposals and estimates, delivery methods and accelerators, and pre-sales support.