Senior Data Engineer R

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
2. 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
3. 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
4. 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)
5. 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
6. Monitoring & Reliability
Build logging monitoring and alerting for pipelines
Troubleshoot failures and optimize performance
Ensure high availability and fault tolerance
7. 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
Bachelors degree in Computer Science Engineering or related field
48 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

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