A Day in the Life
As aSenior Data Engineer - Techno-Manager, you will:
- Lead the end-to-end data engineering efforts, ensuring efficient data pipelines, ETL processes, and data governance practices.
- Architect and optimize data solutionsinSnowflake, Azure, and other cloud platformsfor enterprise analytics and AI/ML models.
- Collaborate with Data Scientiststo design and implement scalable machine-learning pipelines.
- Oversee Power BI development, ensuring efficient data modeling and visualization best practices.
- Manage stakeholder expectationswhile delivering high-quality, reliable, and scalable data solutions.
- Mentor and guide junior engineers, fostering best practices in coding, architecture, and data pipeline automation.
- Ensure data integrity, security, and compliancewhile working with structured and unstructured data sources.
- Work closely with business and IT teamsto drive automation, self-service analytics, and cloud-based transformations.
- Engage with USA teamsfor strategic discussions, project updates, and technical alignment .
As aPeople Manager, you will provide leadership, coaching, and career development opportunities to your team members. You will foster a culture of innovation, continuous learning, and collaboration, ensuring that team members have the resources and guidance needed to succeed in their roles. You will also facilitate communication between global teams and ensure that the team is aligned with business objectives.
This role requires2-3 hours of overlap with USA teams, typically during early mornings or late evenings, to align with project requirements, attend stakeholder meetings, and ensure smooth collaboration across different time zones.
Must Have: Minimum Requirements
- Bachelor s or Master s degreein Computer Science, Engineering, Data Science, or related field.
- 10+ years of experiencein Data Engineering, Big Data, or Cloud Data Technologies.
- Strong expertise in Snowflake, SQL, Python, and ETL processes.
- Experience in Power BI(data modeling, DAX, performance optimization, and visualization best practices).
- Cloud experience with Azure, AWS, or GCP, including data lakes, warehousing, and orchestration tools.
- Experience with modern data stack(Databricks, Apache Spark, Airflow, etc.).
- Exposure to AI/ML modelsand working with Data Scientists for productionizing models.
- Strong problem-solving and communication skillswith a global mindset.
- Ability to balance technical depth with stakeholder engagement and people management.
Nice to Have
- Experience inSnowflake performance tuningand cost optimization.
- Hands-on experience withCI/CD pipelinesfor data engineering workflows.
- Knowledge ofAPIs and integration with enterprise applications.
- Prior experience leading small teams or mentoring engineers.
- Familiarity with SAP, ERP, OneStream or other enterprise data sources.
