This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineering Manager based in India.
This role leads a high-performing data engineering team responsible for building scalable, reliable, and business-critical data solutions.
You will combine people leadership with technical delivery, helping engineers grow while ensuring strong execution and engineering standards.
The position oversees modern cloud data platforms, with a particular focus on AWS and Snowflake environments.
You will work closely with Product, Analytics, Data Governance, and other stakeholders to connect engineering initiatives with strategic business goals.
The role offers significant influence over data architecture, platform scalability, governance, automation, and the broader Data & Analytics roadmap.
You will operate in a collaborative and forward-looking environment where innovation, data quality, security, and cost efficiency are key priorities.
This is an opportunity to shape both the technical direction and culture of a growing data engineering function.
Accountabilities:
- Leadership and People Management: Lead, coach, and mentor a team of data engineers, taking ownership of development plans, performance reviews, career progression, engagement, and a culture of collaboration, inclusion, learning, and psychological safety.
- Technical Delivery: Oversee the design and implementation of scalable, high-quality data pipelines and cloud data platforms using AWS and Snowflake, while partnering with the Principal Data Engineer to maintain strong technical architecture and engineering standards.
- Engineering Excellence: Drive adoption of modern data engineering practices, including CI/CD, Agile delivery, automation, testing, data quality, governance, security, and cost-efficient cloud resource management.
- Data Platform Optimization: Continuously improve data flows, pipelines, and platform capabilities to support business analytics, personalization, and advanced data products while maintaining reliability and scalability.
- Strategic Stakeholder Engagement: Partner with Product Owners, Data Governance, Analytics, and other stakeholders to align engineering priorities with strategic data objectives and communicate complex technical solutions clearly to both technical and non-technical audiences.
- Roadmap and Transformation: Contribute to the Data & Analytics roadmap and lead initiatives such as platform migrations, architecture redesigns, automation improvements, and pipeline optimization to support future growth.
- Cross-Functional Influence: Represent data engineering in cross-functional forums, advocate for modern data practices, and help drive data-informed decision-making and scalable solutions across the organization.
Requirements
- People Leadership: Proven experience leading and developing high-performing data engineering teams, ideally within hybrid or distributed environments, with strong skills in coaching, performance management, career development, and team engagement.
- Data Architecture: Deep understanding of modern data architecture patterns including Data Lakes, Data Warehouses, Lakehouses, and Data Mesh, combined with experience designing and delivering cloud-based data platforms.
- Cloud and Data Engineering: Strong experience with AWS and Snowflake, as well as ETL/ELT development, orchestration, and automation using technologies such as AWS Glue, Step Functions, Airflow, or dbt.
- Programming and Automation: Strong Python and SQL skills, including testing, optimization, CI/CD integration, and experience with infrastructure-as-code technologies such as Terraform or CloudFormation.
- Advanced Data Technologies: Experience with streaming and event-driven architectures such as Kafka or Kinesis, data observability, and data modeling across dimensional, canonical, and semantic models.
- Governance and Security: Solid understanding of data governance, privacy, security, data lineage, access controls, and regulatory requirements such as GDPR.
- Delivery Management: Demonstrated success delivering data solutions using Agile methodologies such as Scrum or Kanban, with the ability to balance delivery speed, quality, scalability, and cost.
- Strategic Communication: Excellent communication and influencing skills, with the ability to translate complex technical concepts into clear business language and connect engineering initiatives to business value.
- Leadership Mindset: High accountability, resilience, adaptability, and a strategic approach to driving innovation and modern data practices across a fast-moving organization.
Benefits
- Hybrid Work: Flexible hybrid work arrangement combining remote and office-based work.
- Annual Leave: 26 calendar days of annual leave.
- Health Insurance: Health insurance coverage as part of the benefits package.
- Maternity Leave: Six months of paid maternity leave.
- Paternity Leave: 15 days of paid paternity leave.
- Career Growth: Opportunity to lead a growing data engineering function while contributing to strategic data transformation and innovation initiatives.
- Inclusive Environment: A collaborative workplace focused on inclusion, professional growth, meaningful work, and enabling employees to reach their full potential.
- Compensation: The role offers a competitive salary and benefits package; a specific salary range was not provided.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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