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 DescriptionProject – 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.
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.
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.
Skills Required
- 5+ years of data engineering experience
- At least 2 years of hands-on Spark development, preferably PySpark
- Deep knowledge of Delta Lake internals, including transaction logs, checkpoints, retention, VACUUM, OPTIMIZE, deletion vectors, and statistics collection
- Expertise with Parquet footers, statistics allowlists, row-group sizing, dictionary encoding, and column indexes
- Hands-on Microsoft Fabric experience with workspaces, capacities, notebooks, lakehouses, semantic models, Direct Lake, and SQL analytics endpoints
- SQL performance tuning for OLAP and OLTP workloads, including Fabric and PostgreSQL
- Strong Python data engineering skills with pandas, PyArrow, and delta-rs
- Ability to communicate architecture clearly in writing
- Ability to work autonomously on well-scoped features
- PCI-scoped data platform experience
- Financial services or payments domain experience
- Power BI semantic model authoring and DAX
- Familiarity with data-standard governance patterns, SCD2 dimensions, natural-key idempotency, and extension attribute stores
- OneLake shortcuts and cross-workspace lakehouse experience
- ClickHouse or similar OLAP engine familiarity
- Terraform for Azure data resources
- Experience with fluid or schema-flexible ingestion patterns
Software Mind Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Software Mind and has not been reviewed or approved by Software Mind.
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Fair & Transparent Compensation — Pay is considered competitive for core hiring markets, with “good salary” cited in multiple locales. Public salary snapshots provide a baseline that helps candidates assess offers and negotiations.
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Flexible Benefits — Remote or hybrid options are prominently highlighted, and a remote‑work program is publicly noted alongside positively cited work‑from‑home experiences. Flexibility around schedules and location is presented as part of the package.
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Wellbeing & Lifestyle Benefits — Private medical care, language classes, sports/fitness support, and learning initiatives are listed for several Central/Eastern European locations, with occasional workation perks promoted. These lifestyle‑oriented offerings complement base pay and can enhance perceived total rewards.
Software Mind Insights
What We Do
Software Mind is a global digital transformation partner with operations throughout Europe, the US and LATAM. Driven by tech and empowered by people, we provide companies with software engineers and autonomous, cross-functional development teams who manage software life cycles from ideation to release and beyond. For over 20 years we’ve been enriching organizations with the talent they need to boost scalability, drive dynamic growth and bring disruptive ideas to life. Our top-notch engineering teams combine ownership with leading technologies, including cloud, AI, data science and embedded software to accelerate digital transformations and boost software delivery. A culture, driven by trust, that embraces openness, craves more and acts with respect enables our experts to create evolutive solutions that support scale-ups, unicorns and enterprise-level companies around the world.








