Senior Databricks Data Engineer

Position Overview We are looking for a Senior, Super Hands-On Databricks Data Engineer who lives and breathes code, query optimization, and modern data architecture. In this role, you won't just design architectures on whiteboards—you will write production PySpark/SQL, optimize Databricks clusters, build streaming and batch pipelines, and enforce data governance. You will own end-to-end pipeline execution from raw ingestion to curated Gold layer models, playing a lead role in modernizing our Lakehouse platform. Key Responsibilities 1. Hands-On Pipeline Development & Lakehouse Architecture Design, build, and maintain enterprise-scale batch and real-time streaming pipelines using PySpark, SQL, Delta Live Tables (DLT), and Auto Loader. Implement and refine Medallion Architecture (Bronze Silver Gold) to support downstream BI, reporting, and Machine Learning workloads. Enforce schema evolution, ACID transactions, and data compaction using Delta Lake core constructs. 2. Performance Tuning & Optimization (Deep Tech) Diagnose and resolve Spark performance bottlenecks: data skew, OOM errors, excessive shufflings, and memory spills. Optimize queries using Liquid Clustering, Z-Ordering, Data Partitioning, AQE (Adaptive Query Execution), and Photon engine tuning. Benchmark and optimize Databricks compute workloads to minimize DBU (Databricks Unit) consumption and cloud costs (FinOps). 3. Governance, Security & Quality Implement end-to-end data governance, fine-grained access control (row/column-level security), and lineage tracking using Unity Catalog. Automate automated data quality validation checks and alert mechanisms across the pipeline life cycle. 4. Operations, CI/CD & DevOps Automate pipeline orchestration using Databricks Asset Bundles (DABs) or Databricks Workflows / Apache Airflow. Build CI/CD pipelines (GitHub Actions, Azure DevOps, or GitLab) for automated testing, deployment, and code promotions. Requirements Required Skills & Qualifications Must-Haves Experience: 8+ years in Data Engineering, with 4+ years of intensive, hands-on production experience on Databricks. Programming Mastery: Fluent in PySpark, Advanced SQL, and Python. Databricks Ecosystem: Deep experience with Delta Lake, Unity Catalog, Delta Live Tables (DLT), Auto Loader, and Databricks Workflows. Cloud Infrastructure: Strong hands-on experience in at least one primary cloud provider (AWS, Azure, or GCP) integration with Databricks (S3/ADLS Gen2, IAM, Key Vaults/Secret Manager). Data Modeling: Solid understanding of dimensional modeling (Kimball), One Big Table (OBT) strategies, and data vault patterns. CI/CD & Software Engineering: Proficient in Git workflows, unit testing PySpark code (pytest), and deployment automation. Preferred / Nice-to-Haves Certifications: Databricks Certified Data Engineer Professional. Streaming: Hands-on with Apache Kafka, Event Hubs, or Kinesis integration via Structured Streaming. GenAI / ML Ops: Familiarity with MLflow, Feature Store, or Vector Search within Databricks. Infrastructure as Code (IaC): Experience using Terraform to provision Databricks workspaces and storage resources. Performance Indicators (How success is measured) Pipeline Reliability: Maintaining strict SLA thresholds on critical Gold-layer models. Cost Efficiency: Measurable reduction in DBU costs through effective compute profiling and tuning. Code Quality: High test coverage and zero-downtime CI/CD deployments.

Design and maintain enterprise-scale batch and streaming pipelines using a Medallion Architecture on a Databricks Lakehouse platform. Optimize Spark performance and implement data governance and security via Unity Catalog.

Requires over 8 years of data engineering experience, with at least 4 years of intensive production experience in Databricks. Mastery of PySpark, SQL, and Python is essential, along with proficiency in CI/CD and cloud infrastructure.

• CI/CDSouhaitée
• PythonSouhaitée

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• PySpark
• Advanced SQL
• Python
• Databricks
• Delta Lake
• Unity Catalog
• Delta Live Tables
• Auto Loader
• Medallion Architecture
• Spark Performance Tuning
• CI/CD
• Data Modeling
• Cloud Infrastructure
• Apache Airflow
• GitHub Actions
• Azure DevOps

• Data & Analytics
• Technology
• Software
• Engineering
• Transportation

Expérience minimale

10+ ans

Postuler avant le

12 sept. 2026

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Niveau d’expérience

Mid-Senior level

Mode de candidature

La candidature directe est offerte