Data Engineering Manager Data, BI & Analytics · Mumbai ·

Collinson is a global loyalty and benefits company.

Collinson is a privately-owned entrepreneurial business with 2,000 passionate people working in 20 locations worldwide. Our solutions include Priority Pass, the world’s best known airport experiences programme, while we are also the trusted partner behind many of the leading financial services, airline and hotel brand’s reward programmes and loyalty initiatives.

We take our 30 years’ experience working with these kinds of household names in over 170 countries, and help our clients to deliver the smarter experiences it takes to differentiate their propositions, and help them win deeper devotion with their customers.

Purpose of the job

We are seeking a Data Engineering Manager who is passionate about building great teams, shipping products fast, and fostering an inspiring engineering culture. You’ll be the kind of person who loves to see data engineers grow, removes obstacles before they become problems, and knows that the best teams deliver not because of deadlines, but because they’re truly engaged in what they’re building. You will partner closely with our Principal Data Engineer to ensure a balanced approach across execution excellence, career progression, technical innovation, and delivery discipline.

You’ll bring a strong technical background and have been hands-on with data engineering and building data products. You get how engineers think, and how to help them thrive. You believe in iterating fast, learning from failure, and building scalable, maintainable systems without getting bogged down in bureaucracy.

This role requires a leader who is technically credible, but who also thrives on building an empowered, high-performing team. You’ll manage and mentor data engineers, align delivery to business needs, and champion both engineering quality and personal development.

• 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.

• 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.
• Strategic & Communication Skills
• 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.