ADG Senior Analyst (Data Engineer-Databricks & Pyspark)

About the Company

Essex Lake Group LLC

With global headquarters in New York, U.S.A. and operations in India, Canada, China and the United Kingdom, Essex Lake Group LLC (Essex) delivers transformative profit enhancing solutions, anchored on insights from Big Data, Advanced Analytics and its extensive executive and industry experience. Essex'customized battle-tested solutions deliver a measurable positive impact within 6 to 18 months. Essex solutions have created substantial profit increases for clients in the areas of revenue growth, cost reduction, consumer and enterprise risk management regulatory compliance. Every Essex solution is customized for the client and the specific problem or opportunity. Essex has proven success and specific experience in the Financial Services, Retail Banking, Telecommunications, Insurance, Healthcare and Media & Entertainment industries, as well as others. Essex delivers visibility in complex businesses to help clients make sound business decisions and its experienced industry experts work with clients through full implementation of its solutions to ensure the organization receives all the benefits from its solutions and methodologies. Further information on the company can be found on its website: www.essexlg.com

About the Role

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.

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

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