Data Engineer (NCS/Job/ 2905)

Job Description: Sr. Data Engineer (2-4 Years)

Role Summary

As a Sr. Data Engineer, you will be part of high-performing delivery teams supporting data modernization, migration, and analytics transformation programs for global clients. You will contribute to the design, development, and implementation of scalable data engineering solutions, working across the full data lifecycle in complex, multi-system environments.

Key Responsibilities

• Contribute to the design and development of end-to-end data engineering pipelines across ingestion, transformation, and consumption layers.
• Develop and optimize ETL/ELT workflows to support enterprise reporting and advanced analytics use cases.
• Execute data migration initiatives, including source-to-target mapping, data validation, reconciliation, and performance tuning.
• Build scalable data processing solutions using Apache Spark and PySpark.
• Develop complex SQL-based transformations and ensure data accuracy, consistency, and integrity.
• Support data quality, governance, and control frameworks aligned with client and regulatory requirements.
• Collaborate with cross-functional teams including architects, analysts, QA, and client stakeholders to gather requirements and deliver solutions.
• Participate in Agile delivery models, including sprint planning, stand-ups, reviews, and retrospectives.
• Prepare technical documentation and support knowledge transfer activities.
• Adhere to firm-wide delivery excellence, security, and compliance standards.

Required Skills & Experience

• 2+ years of relevant experience in Data Engineering, Data Platforms, or Analytics Engineering
• Exposure to AWS cloud services such as S3, Glue, EMR, Redshift, Athena, or Lambda.
• Strong hands-on experience in SQL, Python, and PySpark
• Hands-on experience with Databricks and/or AWS EMR
• Experience in data validation and data quality checks
• Strong knowledge of data modelling (fact and dimension tables)
• Ability to debug, optimize, and performance-tune Spark and SQL jobs
• Experience building KPI, reporting, and analytics datasets

Good to Have

• Familiarity with data lake and data warehouse architectures.
• Experience with workflow orchestration tools (Airflow, Step Functions, etc.)
• Experience with CI/CD pipelines and Git-based development workflows

Education & Certifications

• Bachelor’s degree in engineering, Computer Science, or a related discipline.
• Cloud or data-related certifications (AWS, Azure, GCP) are an added advantage.

Professional Attributes

• Client-focused mindset with the ability to work in consulting-driven delivery environments
• Ability to work effectively in deadline-driven settings
• Strong documentation, communication, and collaboration skills