TELECOMMUTE Data Engineer

Mphasis
United States
14 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Working hours
Regular working hours
Job source

Tech stack

Amazon Web Services Amazon S3 Computer Programming Databases Information Engineering Data Infrastructure Extract Transform Load (ETL) Data Transformation Data Security Software Debugging Monitoring of Systems Python (Programming Language)
+16 more
PostgreSQL MySQL Performance Tuning Query Optimization SQL Databases Management of Software Versions Data Processing Scripting Data Storage Management Data Ingestion Pyspark AWS Glue AWS Data Analytics Data Pipelines Serverless Computing Amazon Redshift

Job description

We are seeking a skilled, experienced and motivated Data Engineer with expertise in AWS services such as S3, Redshift, Glue, Step Functions, and Lambda to join our support team. The ideal candidate will be responsible for managing, monitoring, and troubleshooting data pipelines and workflows, ensuring the seamless operation of data infrastructure, and providing ongoing support to maintain data availability and integrity., AWS Data Pipeline Maintenance: Monitor and troubleshoot data pipelines and workflows utilizing AWS Glue, Step Functions, and Lambda. Optimize existing data pipelines for performance and cost efficiency.

Data Storage Management: Manage and support data stored in Amazon S3 and ensure 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.

Issue Resolution: 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.

Performance Optimization: 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.

Data Quality and Governance: Implement monitoring tools and dashboards to track data pipeline health. Collaborate with stakeholders to ensure adherence to data security, governance, and compliance policies.

Documentation and Reporting: Maintain up-to-date documentation for data pipelines, workflows, and troubleshooting steps. Provide regular reports on system performance and key metrics.

Collaboration and Support: 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 yrs in Data engineering with relevant skills

Mandatory Skills:

AWS Services (S3, Redshift, Lambda, Glue, Step function) Python

Technical Expertise:

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.

Database Knowledge:

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.

Programming Skills:

Proficiency in Python for scripting, data manipulation, and building serverless applications with Lambda.

Knowledge of PySpark or similar frameworks is a plus.

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