Description

Key Responsibilities

1. Build reusable Python-based data engineering frameworks, ingestion libraries, Dagster/dbt components, templates, and shared tooling for our Data Platform.
2. Design and implement standardized ingestion patterns for RDBMS, APIs, files, ADLS, Snowflake, and other enterprise data sources.
3. Develop scalable and maintainable ELT/ETL pipelines using Python, Dagster, dbt, and SQL.
4. Create reusable data transformation patterns, data quality controls, testing frameworks, and metadata-driven engineering approaches.
5. Design and optimize data models, transformation workflows, and analytics-ready datasets that support business and AI use cases.
6. Improve developer productivity through reusable frameworks, documentation, standards, templates, and self-service engineering capabilities.
7. Drive engineering best practices around code quality, testing, version control, CI/CD, observability, and deployment automation for data workloads.
8. Troubleshoot and resolve complex data integration, pipeline performance, orchestration, and production data issues across the platform.
9. Support Snowflake-based data engineering solutions, including performance optimization, data governance practices, monitoring, and operational support.
10. Act as a senior technical leader and mentor for Data & AI Engineers, Analytics Engineers, and product teams, helping establish scalable engineering standards and practices.

Enable Skills-Based Hiring No ECMS REQ IDAdditional Details

- ECMS REQ ID : 584889
- Project Location 1 : Pan India
- Project Location 2 : (No Value)
- Project Location 3 : (No Value)
- Project Location 4 : (No Value)
- Delivery SPOC : Aru Talwar
- Relevant Experience : 5 - 8
- Mandatory skills : 1. Expert-level Python development experience, including building reusable Python packages, data processing frameworks, SDKs, and production-grade data engineering solutions.2.



Strong experience designing and developing complex ETL/ELT pipelines using Python and modern data engineering practices.3. Hands-on experience with Dagster, Airflow, or similar workflow orchestration platforms.4. Strong SQL skills and experience building scalable analytical data models using dbt or similar transformation frameworks.5. Snowflake or equivalent cloud data warehouse experience, including performance tuning and optimization.6. Experience integrating data from APIs, databases, files, and enterprise systems at scale.7. Experience implementing data quality, testing, lineage, observability, and monitoring frameworks.8. Familiarity with CI/CD practices and version-controlled deployment approaches for data engineering workloads.9. Strong problem-solving and debugging skills across data pipelines, transformations, orchestration processes, and production environments.10. Ability to work independently and create explicit technical documentation, standards, reusable patterns, and engineering frameworks.
- Desired skills : • Azure data services experience, including ADLS, Azure Data Factory, Event Hub, Service Bus, or related services.• Experience with DataOps, data governance, lineage, cataloging, and metadata management practices.• Exposure to streaming and real-time data processing technologies.• Experience supporting machine learning, AI, or advanced analytics data platforms.• Familiarity with Kubernetes, Docker, or cloud-native technologies used to support modern data platforms.• Experience with data observability and monitoring tools such as Grafana, Azure Monitor, Monte Carlo, or comparable solutions.
- Domain (Industry) : Telecom
- BGC (Before onboarding / After onboarding) : PostOB
- Total Experience (Ex. 5-7 Years) : 5 - 8
- BGC Details : NA
- BGC Vendor : Na
- Mode of Interview : Face to Face
- WFO / WFH / Hybrid : Hybrid
- Please enter shift timings : 11
- Shift Timings : General

📌 584889 _ DNACMT _ Sr Data Engineer _ India
🏢 Trigent Software
📍 India