Key Responsibilities
Design, develop, and support batch and incremental data ingestion pipelines into the data lake.
Develop and optimize complex SQL queries, data transformations, and ETL workflows.
Build, maintain, and monitor Airflow DAGs for orchestration and workflow automation.
Analyze and troubleshoot data quality, data reconciliation, and pipeline execution issues.
Perform end-to-end data lineage analysis and trace data from source systems to downstream consumers.
Debug data discrepancies by investigating source systems, transformation logic, and target datasets.
Support data migration and modernization initiatives from legacy platforms to cloud-based data platforms.
Work closely with business stakeholders, architects, and upstream/downstream teams to understand data requirements.
Validate data completeness, accuracy, and consistency across multiple systems.
Participate in production support activities and resolve data-related incidents within SLA timelines.
Develop reusable data engineering components and recommend process improvements.
Required Skills
Strong Expertise
SQL / PL/SQL
Complex joins, CTEs, analytical functions
Query optimization and performance tuning
Data modeling and database concepts
BigQuery
Query development and optimization
Partitioning and clustering concepts
Data loading and transformation techniques
ETL/Data Engineering
Data ingestion patterns (Batch and Incremental)
Data transformations and validations
Data quality checks and reconciliation
Good to Have
Apache Airflow
Developing and troubleshooting DAGs
Scheduling, monitoring, and dependency management
Python
Basic to intermediate scripting
Data processing and automation
Cloud Platforms (Preferably GCP)
Cloud Storage
BigQuery
Composer/Airflow
Preferred Candidate Profile
Strong analytical and problem-solving skills.
Ability to independently investigate and resolve data issues.
Good communication and stakeholder management skills.
Experience in cloud data lake or warehouse environments.
Exposure to customer, transactional, or enterprise-scale datasets is preferred.
Screening Focus Areas
Advanced SQL/PLSQL
ETL & Data Pipeline Design
BigQuery Concepts
Data Debugging & Root Cause Analysis
Airflow DAG Development
Python Basics
Data Migration & Data Validation
Source-to-Target Traceability and Data Lineage
Must Have: SQL/PLSQL, BigQuery/Cloud Data Warehouse, ETL, Data Analysis & Debugging
Good to Have: Airflow DAG Development, Python, GCP Services
Kafka, Pub/Sub optional
At Zensar, we’re “experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus.
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We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.
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