Role Title: Sr. Data Engineer (ETL/ELT)

Experience Level: 512 years

Education Qualification: BE, BTech, MCA

IC Level: IC3 / IC4

Location: Hyderabad (60%) / Bangalore (40%)

Key Responsibilities:

- Design, develop, and maintain scalable, production-grade ETL/ELT data pipelines using modern orchestration frameworks including Apache Airflow, Apache Spark, Kafka, and MuleSoft.
- Build data ingestion solutions from diverse enterprise source systems including ERP platforms (SAP, Oracle), CRM platforms (Salesforce, Workday), and cloud data warehouses, extracting data via APIs, connectors, and direct database access.
- Develop and maintain analytical content including business metrics, KPIs, and dashboards that drive measurable enterprise outcomes.
- Implement data modelling best practices across relational, dimensional, and cloud warehouse schemas to support downstream analytics consumption.
- Build and maintain data quality frameworks, validation rules, and observability/monitoring pipelines to ensure high-quality, trustworthy data across all product applications.
- Optimize data processing workflows for performance, reliability, and cost-efficiency in cloud-native environments (AWS, Azure, GCP).
- Collaborate with BI Engineers, Data Modellers, Product Managers, and UX Designers to ensure seamless data flow from source systems through transformation layers to analytical dashboards and AI-ready datasets.
- Write clean, reusable, and well-tested code following software engineering best practices including code reviews, unit testing, and CI/CD.




- Work with product owners to understand detailed requirements and own code from design through implementation, test automation, and high-quality delivery.
- Implement software that is extensible and allows customers to customize functionality to meet their specific needs.
- Integrate AI tools and AI-driven approaches actively into engineering workflows, pipeline development, and problem-solving not just as a tool user, but as a critical thinker about where AI adds value.

Required Qualifications:

1.

Experience &

- Core Engineering:
- 512 years of proven track record in building production-grade data pipelines and ETL/ELT solutions at enterprise scale.
- Robust proficiency in Python for data engineering including PySpark, pandas, SQLAlchemy, and data processing libraries.
- Advanced SQL skills: complex joins, window functions, query optimization, performance tuning, and analytical query design.
- Hands-on experience with cloud platforms (AWS, Azure, or GCP) and cloud-native data services.

2. Data Infrastructure &

- Tooling:
- Proficiency with orchestration frameworks: Apache Airflow, Apache Spark, Kafka, MuleSoft, or equivalent.
- Hands-on experience with modern data warehouses and lakehouses: Snowflake, Databricks, BigQuery,



or Redshift including data modelling, optimization, and cost management.
- Working knowledge of ERP/CRM system integrations: SAP, Oracle, Salesforce, Workday extracting data via REST APIs, database connectors, or certified adapters.

3. Analytics &

- Data Modelling:
- Experience building analytical content: metrics, KPIs, dashboards, and data products that directly serve business decision-making.
- Solid understanding of data quality principles, testing frameworks, and data validation methodologies.
- Familiarity with any analytics and data visualization tools such as Tableau, Looker, or Power BI and how they integrate into data workflow solutions.

4. AI &

- Collaboration:
- Demonstrated experience leveraging or critically thinking about AI integration in data engineering workflows, decision-making, and problem-solving including using AI-powered tools, automating workflows, or evaluating AI's impact on data pipelines.
- Strong communication, collaboration, and technical skills to work effectively within cross-functional product engineering teams.

Nice-to-Have Qualifications:

- Active use of AI-powered productivity tools such as Cursor, Windsurf, Claude, or GitHub Copilot for accelerated development.
- Hands-on Java experience and working knowledge of enterprise application design patterns.
- Experience working with ServiceNow platform or similar enterprise workflow platforms.
- Experience with containerization (Docker, Kubernetes) and up-to-date CI/CD pipeline practices.

📌 Senior Data Engineer - ETL (India)
🏢 Headventor
📍 India