Senior Data Platform Engineer

Socket.dev

Dallas (TX)

Hybrid

USD 120,000 - 160,000

Full time

6 days ago

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Benefits offered by this job

Health insurance

Health savings account

Dental insurance

Vision insurance

401(k) matching

Life insurance

Paid time off

Parental leave

Disability insurance

Childcare assistance

Education reimbursement

Fitness membership

Volunteer time off

Job summary

Aperia Solutions in Dallas, TX is seeking a Senior Data Engineer to own Bronze/Silver/Gold data architecture on Microsoft Fabric. You will design and optimized Delta pipelines, build Direct Lake models, and enable scalable risk analytics for high-volume payments data.

You'll collaborate with a small senior team, including a tech lead and DevOps, to ship production-grade pipelines and analytics surfaces, while emphasizing reliability and performance at scale.

Qualifications

5+ years data engineering experience with hands-on Spark development.
Deep Delta Lake internals knowledge and Parquet expertise.
Microsoft Fabric experience with lakehouses, Direct Lake, and semantic models.
Strong Python data engineering skills and SQL performance tuning.
Ability to communicate architecture clearly and work autonomously.

Responsibilities

Design Bronze, Silver, and Gold Delta tables with PAN-safe layouts.
Build Fabric Spark notebooks for feature pipelines across windows.
Create per-flavor Silver adapters and canonical MERGE DAGs.
Materialize Gold pipelines for risk scoring and analytics surfaces.
Design Direct Lake semantic models and optimize for performance at scale.
Configure OneLake layouts and cross-workspace lakehouse patterns.
Implement idempotent Delta writes with delta-rs in Python containers.
Collaborate with DevOps on Terraform and Fabric IaC.

Skills

PySpark

Delta Lake

Microsoft Fabric

SQL tuning

Python

Job description

About Aperia Solutions

Aperia Solutions is a leading payments SaaS company headquartered in Dallas, Texas. We build risk management, residuals accounting, compliance, and analytics platforms used by merchant banks, ISOs, payment processors, and other participants in the credit card payments ecosystem. Operating under PCI DSS 4.0 compliance across dual on-premises datacenters (Allen, TX and Chicago, IL) plus Azure cloud, we process high-volume payment data for some of the industry's largest players.

We're in the middle of a significant platform modernization program: a next-generation risk analysis and scoring platform on Microsoft Fabric, an AI-powered ingestion platform, new AI-native applications, and ongoing evolution of the products our clients rely on every day. The teams executing this work are deliberately small and senior, with executive-level support and minimal bureaucracy. Every senior hire is a founding contributor to the architecture and the code.

About the Role

Aperia 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 Aperia's 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.

What You'll Do

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.

What You Bring

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.

Nice to 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.

Why Aperia

Founding-member impact on a strategic platform serving a multi-hundred-million-dollar industry — your architectural decisions carry weight and ship to production.
Direct working relationship with the SVP of Technology; small team; minimal bureaucracy; senior peers.
Genuine engineering culture — technical correctness valued over slideware; extensive design documentation; real design reviews; ADR discipline.
Explicit team commitment to AI-assisted development (Claude Code, Cursor, GitHub Copilot) — treated as a first-class productivity multiplier, not a novelty. Team standards documented and enforced.
Modern tech stack: Microsoft Fabric, AKS, Azure, Airflow, Python, Delta Lake, Kogito/DMN, OpenBao, Kubernetes.

Eligibility Requirements