
Data Engineer
7 days ago
Job Role: Data Engineer
Experience: 5+ years
Mode: Work from office / Hybrid (Kochi)
Job Type: Full-time, Permanent
Notice Period: days
Job Description:
This role is a hands-on position responsible for the build and continued evolution of the data platform, business applications and integration tools. We are looking for a hands-on engineer that can recommend best practices to work with enterprise data. The ideal candidate is going to be a hands-on engineer, and very strong with AWS Products to help build out data pipelines, create jobs, manage the quality of the data warehouse and integrated tools.
RESPONSIBILITIES
Design, develop, and maintain scalable, efficient data pipelines to support ETL/ELT processes across multiple sources and systems
Partner with Data Science, Analytics, and Business teams to understand data needs, prioritize use cases, and deliver reliable datasets and models
Monitor, optimize, and troubleshoot data jobs, ensuring high availability and performance of data infrastructure
Build and manage data models and schemas in Redshift and other data technologies, enabling self-service analytics
Implement data quality checks, validation rules, and alerting mechanisms to ensure trust in data
Leverage AWS services like Glue, Lambda, S3, Athena, and EMR to build modular, reusable data solutions
Drive improvements in data lineage, cataloging, and documentation to ensure transparency and reusability of data assets
Create and maintain technical documentation and version-controlled workflows (e.g., Git, dbt)
Contribute to and promote a culture of continuous improvement, mentoring peers and advocating for scalable and modern data practices
Participate in sprint planning, code reviews, and team retrospectives as part of an Agile development process
Stay current on industry trends and emerging technologies to identify opportunities for innovation and automation
QUALIFICATIONS
5+ years of experience in software/data engineering, with a proven track record of building robust data systems (prior leadership or mentorship experience is a plus)
Advanced Python, including experience building APIs, scripting ETL processes, and automating workflows
Expert in SQL, with ability to write complex queries, optimize performance, and work across large datasets
Hands-on experience with AWS data ecosystem including Redshift, S3, Glue, Athena, EMR, EC2, DynamoDB, Lambda, and Redis
Strong understanding of data warehousing and data modeling principles (e.g., star/snowflake schema, dimensional modeling)
Familiarity with dbt Labs and modern ELT/analytics engineering practices
Experience working with structured, semi-structured, and unstructured data
Knowledge of data governance, quality assurance, and observability tools to ensure data integrity and trust
Proficiency in creating technical documentation, SOPs, and maintaining clear communication with cross-functional teams
A problem-solving mindset, with the ability to take ownership and drive solutions from design to deployment
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