Engineering Manager overseeing software projects and team development for AI solutions at Veritone. Leading engineering practices and cultivating a supportive and innovative team culture.
About the role
- Data Engineering Manager leading and mentoring a data engineering team at Collinson in Mumbai. Fostering collaboration and technical excellence while overseeing data pipeline design and implementation.
Responsibilities
- Lead, coach, and mentor a team of data engineers, focusing on career growth, learning, and engagement.
- Take ownership of people management, including development plans, performance reviews, and progression pathways.
- Partner with the Principal Data Engineer to balance technical depth with delivery accountability, ensuring the team excels in both.
- Foster a culture of collaboration, inclusion, and innovation within the data engineering function.
- Oversee the design and implementation of scalable, high-quality data pipelines on AWS and Snowflake.
- Collaborate with the Principal Data Engineer on technical architecture and standards, ensuring solutions are future-proof and cost-efficient.
- Drive adoption of best practices in data engineering, CI/CD, and agile delivery.
- Ensure compliance with governance, security, and data quality requirements.
- Continuously optimize data flows to support business analytics, personalization, and advanced data products.
- Work with Product Owners, Data Governance, and Analytics teams to align engineering work to strategic data goals.
- Communicate progress and solutions effectively to technical and non-technical stakeholders.
- Represent data engineering in cross-functional forums, advocating for modern, reliable, and business-enabling data solutions.
- Contribute to shaping the Data & Analytics roadmap, ensuring scalability for future growth.
Requirements
- Proven experience leading and developing high-performing data engineering teams, ideally across hybrid or distributed environments.
- Strong focus on people management — setting clear expectations, supporting individual growth, and ensuring structured career progression.
- Ability to foster a culture of learning, inclusion, and psychological safety, empowering engineers to innovate and take ownership.
- Skilled in coaching engineers of varying experience levels, providing both technical mentorship and constructive feedback.
- Experience partnering with a Principal Data Engineer or equivalent to maintain balance between technical excellence and delivery execution.
- Deep understanding of modern data architecture patterns - Data Lake, Data Warehouse, Lakehouse, and Data Mesh.
- Proven experience designing and delivering cloud data platforms (preferably AWS and Snowflake).
- Expertise in ETL/ELT development, orchestration, and data automation using tools such as AWS Glue, Step Functions, Airflow, or dbt.
- Strong programming proficiency in Python and SQL, with experience in testing, optimisation, and CI/CD integration.
- Experience with streaming and event-driven architectures (e.g., Kafka, Kinesis).
- Knowledge of infrastructure-as-code (Terraform, CloudFormation) and data observability best practices.
- Strong background in data modelling (dimensional, canonical, and semantic models) to support analytical and operational use cases.
- Understanding of data governance, security, and privacy principles, including GDPR compliance, data lineage, and access controls.
- Demonstrated success delivering data solutions using Agile methodologies (Scrum/Kanban).
- Skilled at balancing speed, quality, and cost, with awareness of cloud resource efficiency and cost management.
- Experienced in leading both strategic transformation projects (platform migrations, architecture redesigns) and incremental delivery improvements (pipeline tuning, automation).
- Confident in aligning technical delivery with business needs and collaborating closely with Product, Analytics, and Governance teams.
- Excellent communicator — able to explain complex technical solutions in clear, accessible language.
- Strong influencing skills to drive adoption of modern data practices and data-driven decision-making across the business.
- Strategic thinker who connects engineering initiatives with business value, supporting innovation and scalability.
- High accountability, resilience, and adaptability in a fast-moving environment.
Benefits
- Flexible work arrangements
- Professional development opportunities
Job title
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Tech skills
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