Senior Data Specialist - R01565550
Quick Summary
Lead Data Engineer ETL Fundamentals, SQL, SQL (Basic + Advanced), Python, Data Warehousing, Modern Data Platform Fundamentals, Data Modelling Fundamentals, PLSQL, T-SQL,
Brillio is a leading digital transformation partner delivering innovative solutions across Data, Cloud, AI, and Digital Engineering. We help global enterprises unlock value through cutting-edge technology and data-driven insights.
We are looking for a hands-on Data Engineer with strong Databricks expertise to design, build, and scale modern data platforms. The ideal candidate will have experience in PySpark, Delta Lake, and cloud-native data engineering and will work closely with analytics, product, and business teams to deliver high-performance data pipelines.
Responsibilities
~1 min read- →Design, develop, and maintain scalable ETL/ELT data pipelines using Databricks and PySpark
- →Build and optimize data lakehouse architectures (Bronze–Silver–Gold layers)
- →Develop data ingestion frameworks from multiple sources (batch & real-time)
- →Implement Delta Lake features including schema evolution, ACID transactions, and optimization
- →Create and manage Databricks notebooks, workflows, and jobs for production pipelines
- →Ensure data quality, governance, and lineage across pipelines
- →Optimize Spark jobs for performance (partitioning, caching, tuning)
- →Collaborate with cross-functional teams (Data Scientists, Analysts, Architects)
- →Support production deployments, monitoring, and troubleshooting of data pipelines
- →Contribute to migration of legacy data platforms to modern cloud-based architecture
- Strong experience in:
- Databricks (Workflows, Notebooks, Jobs)
- PySpark / Spark SQL
- SQL & Data Warehousing concepts
- Hands-on experience with:
- Delta Lake / Lakehouse architecture
- Data pipeline development & orchestration
- Good understanding of:
- Data modeling, ETL/ELT processes, SCD concepts
- Experience in at least one:
- AWS (S3, Glue, EMR) / Azure (ADF, ADLS, Synapse)
- Workflow tools:
- Airflow / Databricks Workflows
- Version control:
- Git / CI-CD pipelines
- Experience with:
- Streaming frameworks (Kafka / Spark Streaming)
- DBT / Snowflake / Redshift / Fabric
- Exposure to:
- Unity Catalog, Autoloader, Delta Live Tables
- 5–10 years of experience in Data Engineering
- Minimum 2–4 years of hands-on Databricks experience
- Proven experience building enterprise-scale data platforms and pipelines
- Strong problem-solving and analytical skills
- Ability to work in a fast-paced, agile environment
- Good communication and stakeholder management
What We Offer
~1 min readLocation & Eligibility
Listing Details
- Posted
- May 19, 2026
- First seen
- June 22, 2026
- Last seen
- July 9, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 24%
- Scored at
- June 22, 2026
Signal breakdown
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