Tax Consultant II – ETL Engineer – Global Employer Services Technology Center

As a consultant in the Analytics team, you will design, develop, and support scalable ETL and data integration solutions using AWS-native technologies. You will build reliable data pipelines, transform and curate data for downstream consumption, and work closely with analysts, developers, and business stakeholders to deliver high-quality data products. The current technology stack includes AWS Glue, Lambda, S3, and Redshift, with a planned migration to Databricks. This role requires strong hands-on data engineering experience, proficiency in Python and PySpark, attention to data quality, and the ability to manage multiple priorities in a dynamic environment.

Responsibilities:

• At least 3 years of relevant experience in ETL, data integration, or data engineering roles.
• Design, develop, test, deploy, and support scalable batch and near real time data pipelines.
• Build and optimize ETL workflows using AWS Glue, Lambda, S3, and Redshift.
• Develop data transformation logic using Python, PySpark, and SQL, with a focus on performance, reusability, and maintainability.
• Integrate data from databases, files, REST APIs, and other source systems into curated data layers.
• Implement data quality checks, reconciliation, monitoring, error handling, and operational alerting across data pipelines.
• Design and optimize data models, schemas, and complex SQL queries for relational and data warehouse environments.
• Contribute to the planned migration from the AWS-based data platform to Databricks, including pipeline assessment, redesign, and validation.
• Implement and manage CI/CD pipelines using Azure DevOps or similar tools for source control, automated testing, and deployment.
• Collaborate with cross-functional teams to translate business and data requirements into reliable technical solutions that meet quality and delivery expectations.
• Demonstrate strong problem-solving, communication, collaboration, and the ability to work independently while managing multiple priorities.

Education/Background: Bachelor / Master degree in Computer Science Engineering, or a related field.

Location: Hyderabad
Shift Timings: 11:00 AM - 8:00 PM

Key skills desired

• Strong hands-on experience designing and developing ETL/data integration pipelines.
• Hands-on experience with AWS Glue, Lambda, S3, and Redshift.
• Strong Python and PySpark development experience for data ingestion and transformation.
• Strong SQL skills, including writing complex queries, performance tuning, and working with relational databases and data warehouses.
• Hands-on experience with Kafka or comparable event-driven technologies for real-time or near-real-time data transmission and processing.
• Hands-on experience building traditional bulk data ingestion processes from relational databases and CSV/flat files, including full and incremental loads.
• Understanding of data modeling, data quality, reconciliation, orchestration, logging, monitoring, and error-handling practices.
• Familiarity with CI/CD processes and tools, with Azure DevOps preferred.
• Excellent written and verbal communication skills, with the ability to collaborate across technical and business teams.
• Strong critical thinking, troubleshooting, and problem-solving abilities.
• Hands-on experience with Databricks, including notebooks, workflows/jobs, Delta Lake, and lakehouse concepts.
• Experience migrating ETL pipelines and data workloads from AWS services or legacy platforms to Databricks.
• Knowledge of Databricks governance and security capabilities, such as Unity Catalog.
• Experience with containerization technologies such as Docker, Kubernetes, or AWS EKS.
• Experience with legacy ETL and database technologies, including SSIS, SQL Server, and Oracle, and modernizing or migrating those solutions.
• High-level familiarity with reporting and dashboarding tools such as SSRS/Bold Reports, QlikView, or Qlik Sense, to support downstream data consumers.
• Understanding of Agile development methodologies.