[C3A] Senior Data Platform Engineer (Microsoft Fabric)
Software Mind Warsaw, Masovian Voivodeship, Poland
IT Services and IT Consulting · 1,001-5,000 employees
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About the role
Design and implement the Microsoft Fabric medallion data architecture, including Bronze, canonical Silver, and Gold Delta tables, Spark feature pipelines, and idempotent data ingestion and materialization. Build Direct Lake semantic models, optimize physical layouts and Fabric capacity, and collaborate on infrastructure provisioning and potential ClickHouse alternatives.
What they look for
Requirements
Requires at least five years of data engineering experience, including two or more years of hands-on Spark development, with strong knowledge of Delta Lake, Parquet, Microsoft Fabric, SQL, and Python data engineering tools. Candidates should be able to communicate architecture clearly and work autonomously; experience with PCI-scoped platforms, payments or financial services, Power BI, OneLake, ClickHouse, and Terraform is an advantage.
Benefits
Full description
Company Description
Software Mind develops solutions that make an impact for companies around the globe. Tech giants & unicorns, transformative projects, emerging technologies and limitless opportunities – these are a few words that describe an average day for us. Building cross-functional engineering teams that take ownership and crave more means we’re always on the lookout for talented people who bring passion and creativity to every project. Our culture embraces openness, acts with respect, shows grit & guts and combines cooperation with enjoyment.
Job Description
Project – the aim you’ll have
Client is building a next-generation risk analysis and scoring platform on Microsoft Fabric, and this role owns its medallion data architecture end-to-end. You'll design and build Bronze / Silver / Gold Delta tables, Fabric Spark feature pipelines, Direct Lake semantic models, and physical-layout optimizations. This is our highest-utilization engineering role on the project — central to both Phase 1 platform foundation and Phase 2 risk product delivery, working alongside a Senior Technical Lead, Senior DevOps engineer, and mid-level developer.
The platform ingests transaction and merchant data from clients via SFTP and API, tokenizes sensitive PAN data at the ingestion boundary using our reserved-BIN HMAC-derived format-preserving scheme, and lands data in canonical Silver on Microsoft Fabric per our internal canonical spec. You'll build the pipeline that populates canonical Silver via MERGE, consume it via OneLake shortcuts, and materialize risk-specific Gold tables that feed both custom-authored DMN rules and pre-scored Mastercard Brighterion feeds.
Role – how you’ll contribute
- Design and implement Bronze, canonical Silver, and Gold Delta table schemas with PAN-safe physical layout — statistics allowlist configuration, liquid clustering, deliberate retention settings, V-Order optimization.
- Build Fabric Spark notebooks for the feature pipeline (rolling velocity features across 24h / 7d / 30d windows, merchant-level rolling features, hierarchical rollups, cross-merchant features via pan_token joins).
- Author per-flavor-version Silver adapters — one function per flavor, unioned by name, tested against golden fixtures.
- Build the canonical MERGE DAG (Bronze → canonical Silver, idempotent on _natural_key per Aperia's canonical Fabric internal spec v1.4).
- Build the Gold materialization pipeline for both grains (fact_transaction_risk, fact_merchant_risk) with correct score-source stamping and idempotent merge semantics.
- Design and implement Direct Lake semantic models per reporting surface; performance-test against representative data volumes.
- Configure OneLake namespace layouts, workspace catalogs, and cross-workspace shortcut relationships with the residuals programme.
- Establish idempotent Delta write patterns using delta-rs from Python containers (segmented parallel writes with single atomic commit).
- Fabric capacity sizing (F-SKU selection, load testing, Reservation vs PAYG decisions).
- Partner with the DevOps engineer on Fabric IaC (Terraform capacity provisioning plus Fabric REST workspace bootstrap).
- Consult on ClickHouse contingency if Direct Lake latency proves insufficient for client-tier UIs.
Qualifications
Expectations – the experience you need
- 5+ years data engineering experience, with at least 2 years hands-on Spark development (PySpark preferred).
- Deep Delta Lake internals knowledge — transaction log format, checkpoints, retention settings (logRetentionDuration, deletedFileRetentionDuration), VACUUM, OPTIMIZE, deletion vectors, statistics collection.
- Parquet format expertise — footers, statistics allowlists, row-group sizing, dictionary encoding, column indexes.
- Microsoft Fabric hands-on experience — workspaces, capacities, notebooks, lakehouses, semantic models, Direct Lake, SQL analytics endpoint.
- SQL performance tuning skills for both OLAP (Fabric) and OLTP (PostgreSQL) workloads.
- Strong Python data engineering skills — pandas, PyArrow, delta-rs.
- Ability to communicate architecture clearly in writing and to work autonomously on well-scoped features.
Additional skills – the edge you have
- PCI-scoped data platform experience.
- Financial services or payments domain background.
- Power BI semantic model authoring (DAX).
- Familiarity with published data-standard governance patterns — logical model vs physical profile, SCD2 dimensions, natural-key idempotency, extension attribute stores.
- OneLake shortcuts and cross-workspace lakehouse patterns.
- ClickHouse or similar OLAP engine familiarity.
- Terraform for Azure data resources.
- Prior experience with fluid or schema-flexible ingestion patterns.
Additional Information
What we offer:
- Flexible and remote cooperation options
- International projects with leading global clients
- Travels related to international projects
- Non-corporate atmosphere
- Access* to language classes
- Access* to knowledge-sharing initiatives
- Access* to private healthcare and life insurance
- Access* to multisport card
*The availability and terms of individual benefits may vary depending on the chosen form of cooperation.
