Data Engineer - Apache Spark - Bangalore

Hi,
We are having opening for Data Engineer - Apache Spark - Bangalore

Job Summary:
We're looking for a Junior Data Engineer with strong data architecture and system design skills to design, build, and own end-to-end production pipelines powering analytics and decision-making across the org. The role centers on deep Python + SQL expertise, robust transaction-level fact tables, and rigorous data quality and auditability, ideally within a finance, risk, or compliance data domain.

Working Days: Monday Friday
Job Timing: General (9am to 5pm);
Night shift (3pm to 12am)

• needs to show they can reason about schema design, indexing strategy, and query performance at scale
• Can they design a data model from scratch
• strong SQL (joins, CTEs, window functions, CASE logic). Python as well
• Migration (DB->DB, schema , etc) - Handling rollback, and data validation.
• Validation, reconciliation, or consistency checks
• Handling transaction records.

Position / DesignationData EngineerQualificationBachelor's degree in Computer Science, Information Technology, Engineering, or a related technical fieldYears of Experience3 to 6 years experience Permanent / Contract (If contract, period ?)Permanent Full TimeOffice / Remote / Hybrid Bangalore Bellandur Hybrid Number of post2GenderMale / FemaleAnnual CTC / Salary20LacSelection Process1- Total 3 Technical round
2- 2 rounds evaluation (we can plan to take this together based on panel availability) & 1 with client Job Role & Responsibility Design, build, and maintain robust, scalable data pipelines for ingestion, transformation, and delivery of data across systems.

Develop and optimize ETL/ELT workflows using Python and SQL, ensuring efficiency, reliability, and performance at scale.

Build and manage large-scale data processing jobs using Apache Spark.

¢ Design and implement data warehousing solutions, including data models (dimensional/relational) that support analytics and reporting needs.

¢ Establish and maintain data quality checks, monitoring, and alerting to ensure accuracy, completeness, and consistency of data.

¢ Build and manage workflow orchestration pipelines (e.g., Airflow) for scheduling and automating data jobs.

¢ Support access governance and metadata management practices to ensure secure, well-documented, and discoverable data assets.

¢ Use Git/version control for code management and collaborative development.

¢ Leverage AI-assisted development tools (e.g., Claude, Cursor) to improve development speed and code quality.

¢ Debug and troubleshoot data pipeline issues, performance bottlenecks, and data discrepancies across the stack.

¢ Build basic dashboards/reports and support ad hoc data pulls using Google Data Studio (GDS), Tableau, and Google Sheets as needed.

¢ Collaborate closely with analytics, product, and engineering stakeholders, clearly communicating technical concepts, timelines, and trade-offs.

Skills SQL
Python
Data Engineering
Apache Spark
Data Warehousing & Data Modeling
Data Quality & Monitoring
Debugging & TroubleshootingJoining DateNeed Immediate to 1 Month Tech Requirements -
¢ Communication - High
¢ SQL - High,
¢ Python - High,
¢ Data Engineering - High,
¢ Apache Spark - High,
¢ Data Warehousing & Data Modeling - High,
¢ Data Quality & Monitoring - High,
¢ Airflow/Workflow Orchestration - Medium,
¢ Access Governance & Metadata Management - Medium,
¢ Git/Version Control - Medium,
¢ AI-Assisted Development (Claude + Cursor) - Medium,
¢ Debugging & Troubleshooting - High,
¢ Data Visualisation (GDS + Tableau + GSheets) - low,
¢ Statistics - NA, Experimentation - NA