Essex Lake Group
ADG Analyst/Senior Analyst (Data Engineer-Databricks & Pyspark)
- Compensation
- Not disclosed
- Location
- Gurugram
- Work setup
- Onsite
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Data engineering
- Posted
Skills
Must have
- Strong hands-on experience with Databricks and PySpark
- Proficiency in Python and SQL
- Experience building ETL/ELT pipelines and working with Data Lake
- Understanding of distributed processing, workflow orchestration and performance tuning
- Working knowledge of the banking domain, including banking data and metrics
- Understanding of data-quality requirements, including validation, completeness, accuracy and consistency
Nice to have
- Experience with Azure-based data platforms
- Familiarity with enterprise data governance and sensitive-data handling
- Experience preparing data for Power BI and machine-learning applications
Full description
Position: ADG Senior Analyst (Data Engineer-Databricks & Pyspark)
Experience- 3-5 Years
Location: Gurgaon, India
Work Mode: Work from Office (Monday- Friday)
Time: 2:00 PM 11:00 PM IST
Role Summary
Design, build and maintain scalable data pipelines and curated datasets to support analytics, new capabilities and technology experimentation in the banking domain. Partner with analytics, business and technology teams to deliver reliable, reusable and governed data assets.
Key Responsibilities
- Develop data ingestion and transformation pipelines using Databricks, PySpark, Python and SQL.
- Integrate data from multiple sources and prepare datasets for reporting, analytics and machine-learning use cases.
- Build reusable transformation components and analytical data models.
- Implement data-quality checks, reconciliation, exception handling and pipeline monitoring.
- Optimize Spark workloads for performance, reliability and cost.
- Apply data security, access controls, lineage and documentation standards.
- Support automated deployment, production troubleshooting and ongoing pipeline maintenance.
- Translate banking business requirements into sustainable data solutions.
Required Skills & Experience
- Strong hands-on experience with Databricks and PySpark
- Proficiency in Python and SQL
- Experience building ETL/ELT pipelines and working with Data Lake
- Understanding of distributed processing, workflow orchestration and performance tuning
- Working knowledge of the banking domain, including banking data and metrics
- Understanding of data-quality requirements, including validation, completeness, accuracy and consistency
Preferred Skills
- Experience with Azure-based data platforms
- Familiarity with enterprise data governance and sensitive-data handling
- Experience preparing data for Power BI and machine-learning applications