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.

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.