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Senior Data Engineer - R01563934

brillio-2 · Bangalore, Karnataka, India

Data Science / AI / Machine LearningSenior LevelQuick applyfull-time22 days ago

About The Role

Senior Data Engineer

Primary Skills

We are seeking a highly skilled Databricks Data Engineer to design, build, and optimize scalable data pipelines and lakehouse architectures. The ideal candidate will have strong expertise in Apache Spark, PySpark, Delta Lake, and modern cloud-based data platforms, with the ability to transform complex business requirements into reliable and performant data solutions.

Location : All Brillio Location

  • Experience:4 to 8yrs
  • 🔧 Key Responsibilities
  1. Data Engineering & Pipeline Development
  • Design and develop scalable ETL/ELT pipelines using PySpark and Spark SQL
  • Build and maintain Databricks workflows (Jobs) for orchestration
  • Implement Delta Live Tables (DLT) for declarative pipeline development
  • Develop and manage batch and streaming data pipelines
  1. Lakehouse Architecture Implementation
  • Design and implement Medallion Architecture (Bronze, Silver, Gold layers)
  • Build curated datasets for analytics and reporting
  • Optimize storage using Delta Lake best practices
  1. Data Ingestion & Integration

Ingest data from multiple sources

Databases (RDBMS, NoSQL)

APIs and streaming platforms (Kafka, Event Hubs)

Files (CSV, JSON, Parquet)

Handle structured and semi-structured data efficiently

  1. Delta Lake & Performance Optimization

Implement

  • ACID transactions
  • Schema enforcement and evolution

Change Data Capture (CDC)

Optimize Spark jobs using

  • Partitioning strategies
  • Caching and broadcast joins
  • File compaction and indexing (Z-ORDER)
  1. Data Quality & Governance
  • Implement data validation and quality checks
  • Ensure compliance with data governance standards
  • Use Unity Catalog for access control and data lineage
  • Maintain auditability and data traceability
  1. Monitoring & Reliability
  • Build logging, monitoring, and alerting for pipelines
  • Troubleshoot failures and optimize performance
  • Ensure high availability and fault tolerance
  1. Collaboration & Delivery
  • Work closely with Data Analysts, Data Scientists, and stakeholders
  • Translate business requirements into data models and pipelines
  • Participate in Agile ceremonies (Sprint planning, stand-ups, retrospectives)
  • ✅ Required Qualifications
  • Bachelor’s degree in Computer Science, Engineering, or related field
  • 4–8+ years of experience in Data Engineering

Strong hands-on experience with

Databricks platform

PySpark and Spark SQL

Delta Lake

Experience with

  • ETL/ELT pipeline development
  • Distributed data processing

Solid understanding of

  • Data modeling (Star/Snowflake schemas)
  • Data warehousing concepts
  • ⭐ Preferred Qualifications

Experience with Delta Live Tables (DLT)

  • Knowledge of CI/CD pipelines (Azure DevOps, GitHub Actions)
  • Experience with streaming frameworks (Kafka, Spark Streaming)

Familiarity with cloud platforms

Azure / AWS / GCP

  • Experience with MLflow and MLOps workflows
  • Domain experience (e.g., Healthcare, Finance, Retail)
  • 🛠️ Technical Skills

Languages: Python, SQL

Frameworks: Apache Spark

Tools: Databricks, Delta Lake, MLflow

Data Formats: Parquet, Delta, JSON, Avro

Orchestration: Databricks Workflows / Airflow

Version Control: Git

  • 💡 Soft Skills
  • Strong problem-solving and analytical thinking
  • Excellent communication skills
  • Ability to work in a collaborative environment
  • Attention to detail and data quality
  • 🚀 Nice-to-Have (Optional Add-ons)
  • Experience with real-time analytics
  • Exposure to data governance tools
  • Certification in Databricks or Cloud platforms

Specialization

  • Databricks Engineering: Senior Data Engineer

Job requirements

  • Databricks Engineer

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