Architect

We are seeking a skilled, experienced, and motivated Data Engineer with expertise in AWS services to join our support team.

About the role

As a Technical Lead for Data Engineering, you will manage, monitor, and troubleshoot data pipelines and workflows, ensuring seamless operation of data infrastructure and providing ongoing support to maintain data availability and integrity.

Responsibilities

• Monitor and troubleshoot data pipelines and workflows utilizing AWS Glue, Step Functions, and Lambda.
• Optimize existing data pipelines for performance and cost efficiency.
• Manage and support data stored in Amazon S3, ensuring efficient storage policies (e.g., lifecycle rules, versioning, and encryption).
• Ensure optimal performance and availability of Amazon Redshift clusters, including schema maintenance and query tuning.
• Respond to incidents related to data failures, latency, or data quality and provide timely resolutions.
• Debug and resolve issues in ETL jobs, data ingestion, and transformations.
• Perform root cause analysis for recurring issues and implement solutions to enhance the reliability of the data ecosystem.
• Identify areas for process improvement and implement automation wherever feasible.
• Implement monitoring tools and dashboards to track data pipeline health.
• Collaborate with stakeholders to ensure adherence to data security, governance, and compliance policies.
• Maintain up-to-date documentation for data pipelines, workflows, and troubleshooting steps.
• Provide regular reports on system performance and key metrics.
• Work closely with data engineering, analytics, and operations teams to resolve issues and gather requirements for enhancements.
• Support ad-hoc data requests and ensure timely delivery of data to business users.

Requirements

• Minimum 7 years of experience in Data Engineering.
• Proficient in AWS services: S3, Redshift, Glue, Step Functions, Lambda.
• Strong understanding of ETL/ELT processes and data transformation.
• Experience with monitoring and debugging data pipelines in a production environment.
• Proficiency in SQL and hands-on experience with Redshift for data modeling and performance tuning.
• Knowledge of other databases (e.g., PostgreSQL, MySQL) is a plus.
• Proficiency in Python for scripting, data manipulation, and building serverless applications with Lambda.
• Knowledge of PySpark or similar frameworks is a plus.
• Any graduation degree.

About Mphasis

Mphasis applies next-generation technology to help enterprises transform businesses globally. Customer centricity is foundational to Mphasis and is reflected in the Mphasis’ Front2Back™ Transformation approach. Front2Back™ uses the exponential power of cloud and cognitive to provide hyper-personalized digital experience to clients and their end customers. Mphasis’ Service Transformation approach helps ‘shrink the core’ through the application of digital technologies across legacy environments within an enterprise, enabling businesses to stay ahead in a changing world.

Work locations: Bangalore, Mumbai, Hyderabad, or Chennai (Offshore); Mphasis location, client location, or WFH (Hybrid, Onsite).