Data Engineer
Mphasis
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Job Description
Key Responsibilities
Technical Leadership & Ownership
- Own the end-to-end data engineering architecture for large-scale AWS data platforms
- Define and enforce data engineering standards, best practices, and governance frameworks
- Lead design reviews, code reviews, and technical decision-making across teams
- Act as the primary technical escalation point for complex data pipeline issues
ETL/ELT Design & Development
- Design, build, and optimize scalable ETL/ELT pipelines using:
- AWS Glue (Jobs, Workflows, Crawlers)
- PySpark / Spark SQL, Snowflake, SnowsQL
- Python-based data processing frameworks
- Implement incremental processing, CDC, and data partitioning strategies
- Develop reusable and modular data pipeline frameworks for enterprise use
Data Lake & Storage Management
- Design and manage data lake architecture on AWS (S3 + Apache Iceberg)
- Implement ACID-compliant data layers using Iceberg
- Optimize storage formats (Parquet, ORC) and data layouts for performance
- Define and enforce data lifecycle, retention, and archival policies
Performance Optimization & Cost Efficiency
- Tune Spark/Glue jobs for performance optimization (memory, partitioning, caching)
- Optimize workloads for cost efficiency in AWS (compute, storage, I/O)
- Monitor and improve pipeline SLAs, throughput, and latency metric
Data Governance & Quality
- Implement data quality frameworks, validations, and reconciliation checks
- Ensure compliance with data governance, lineage, and security standards
- Work with cataloging tools (AWS Glue Data Catalog, etc.) for metadata management
Integration & Orchestration
- Design and manage end-to-end orchestration workflows (Glue Workflows, Step Functions, Airflow if applicable)
- Integrate data across multiple sources (RDBMS, APIs, streaming platforms, files)
- Enable reliable, fault-tolerant, and restartable pipeline execution
Stakeholder Collaboration
- Partner with business, analytics, and AI teams to understand data requirements
- Collaborate with architects and DevOps teams for environment setup and automation
- Provide technical guidance to junior engineers and team members
Team Leadership & Mentoring
- Lead and mentor a team of data engineers
- Drive skill development in Spark, AWS, and modern data architectures
- Ensure adherence to Agile practices and timely delivery of milestones
Required Skills & Experience
Core Technical Skills
- Strong experience in AWS Data Engineering stack:
- AWS Glue, S3, Lambda, IAM, CloudWatch
- Advanced proficiency in:
- PySpark / Apache Spark
- Spark SQL
- Python
- Hands-on experience with Apache Iceberg / modern table formats
- Deep understanding of ETL/ELT design patterns and data pipelines
Data Engineering Expertise
- Experience with data lake and lakehouse architectures
- Strong knowledge of data modeling (star/snowflake schemas)
- Experience with batch and near real-time processing
- Familiarity with file formats (Parquet, ORC, Avro)
Performance & Optimization
- Proven experience in large-scale data processing (TB/PB scale)
- Strong expertise in query optimization, partitioning, and indexing strategies
DevOps & Automation
- Experience with CI/CD pipelines for data workflows
- Knowledge of infrastructure as code (CloudFormation/Terraform) is a plus
- Familiarity with version control (Git) and deployment strategies
Preferred Skills (Good to Have)
- Experience with data orchestration tools (Airflow, Step Functions)
- Exposure to streaming frameworks (Kafka, Kinesis)
- Knowledge of data security (encryption, masking, access control)
- Experience supporting AI/ML data pipelines
- Exposure to BI tools (Power BI, Tableau, Sigma)
Qualifications
- Bachelor's/Master's degree in Computer Science, Engineering, or related field
- 8–12+ years of experience in data engineering, with 3+ years in a technical leadership role
About The Company
Mphasis
A leading applied technology services company, we innovate to deliver service excellence and successful outcomes across sales, delivery and development. With our strategy to be agile, nimble and customer-centric, we anticipate the future of applied technology and predict tomorrow’s trends to keep our clients at the summit in an ever-changing marketplace. Leading with architecture and design, our next-gen solutions enable enterprises to accelerate on their digital transformation journey. Customer centricity is foundational to us and is reflected in the Mphasis’ Front2Back™ (F2B) transformation approach. F2B is a customer-in view approach that uses our industry-specific X2C2TM framework, and harnesses the power of cognitive technologies and rich data resident in enterprises to transform them. It is a way to introduce disruptive technology to smartly transform legacy environments. . 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. Mphasis’ core reference architectures and tools, speed and innovation with domain expertise and specialization are key to building strong relationships with marquee clients. Click here to know more Mphasis Presents #HowGeekAreYou Passion, Perseverance, Perfection – we are defined by these three words. Relentless in our pursuit of knowledge, we believe in accepting the difference and defining the 'new normal', staying true to our vision and values. We believe in growth by knowledge, responsibility by authority and freedom by flexibility. Be a part of a place where ideas are celebrated and perseverance is worshiped. Our doors are wide open, and breakthrough ideas are welcome from anyone. But we have a question to ask before we let you in: How Geek Are You? Click here to know more.
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