Lead Data Engineer

Air Arabia; Maharashtra; On-site; INR 2,800,000 - 4,000,000; Full time

Job summary

Air Arabia is seeking a Data Engineering Lead to drive the design and evolution of the data platform, delivering scalable pipelines and lakehouse architectures for analytics and AI workloads.

You will mentor a team of data engineers, partner with data science and AI groups, and ensure governance and security across data assets, while aligning engineering strategy with business objectives.

Qualifications

• Bachelor's or Master's degree in Computer Science/Engineering or related field.
• Proficiency in SQL and Python; strong Spark/Scala/Java knowledge.
• Extensive experience with cloud data platforms (AWS/GCP/Azure).
• Ability to design complex data models across relational, NoSQL and lakehouse.
• Hands-on with data orchestration tools: Airflow, Prefect, dbt; CI/CD for data pipelines.
• Strong data governance, metadata management and security fundamentals.
• Knowledge of MLOps patterns for ML workloads and AI data needs.
• Excellent communication to non-technical stakeholders and leadership.
• Proven leadership in building and mentoring engineering teams.
• Fluent English; Hindi is an advantage.

Responsibilities

• Define and own the data engineering roadmap aligned with AI goals.
• Architect scalable data pipelines, data lakes, and warehouse platforms.
• Lead end-to-end delivery of data engineering initiatives.
• Enforce engineering standards, code quality, and governance.
• Evaluate new tools and cloud-native technologies to improve platform.
• Collaborate with Data Science/AI teams for analytics workloads.
• Translate data requirements into robust engineering solutions.
• Mentor and develop a high-performance data engineering team.
• Own data platform reliability, monitoring, and incident response.
• Provide direction on data security and access control in governance context.

Skills

SQL

Python

Spark

Scala/Java

Cloud Platforms

Data Modeling

Airflow

Prefect

dbt

CI/CD for data pipelines

Data Governance

MLOps

Stakeholder Communication

Leadership

Commercial Awareness

English Proficiency

Hindi Proficiency (advantage)

Education

Bachelor's or Master's in CS/CE/IT

Tools

Apache Airflow

Prefect

dbt

Apache Kafka

Flink

Kinesis

Job description

Job Purpose

Lead the Data Engineering function, owning the design and evolution of the organization's data infrastructure and platform. Drive the delivery of scalable, reliable data pipelines and systems that underpin analytics, data science, and AI capabilities, while developing team capability and aligning engineering strategy with broader business objectives.

Key Result Responsibilities

• Define and own the data engineering roadmap, aligning pipeline, platform, and infrastructure strategy with organizational data and AI goals
• Architect and oversee the design of scalable, resilient data pipelines, data lakes, and warehouse solutions that meet performance, cost, and governance requirements
• Lead end-to-end delivery of complex data engineering initiatives, from requirements through to production
• Establish and enforce engineering standards, code quality practices, and data governance frameworks across the team
• Evaluate and introduce new tools, frameworks, and cloud-native technologies to continuously improve the data platform
• Partner with Data Science and AI teams to ensure data infrastructure is fit for advanced analytics and machine learning workloads
• Collaborate with business stakeholders to translate data requirements into robust, reusable engineering solutions
• Lead, mentor, and develop a team of data engineers, supporting career growth and building a high-performance engineering culture

Key Result Responsibilities-Continued

• Own data platform reliability, monitoring, and incident response; drive root‑cause resolution and preventive improvements
• Provide direction on data security, access control, and compliance in coordination with relevant governance functions

People Management

• Provides direction, coaching and guidance to team members for their career and professional development.
• Creates a conducive working environment to build and sustain a performance driven, engaged, and committed team.
• Ensures people management responsibilities are handled effectively in line with company procedures.

Qualifications (Academic, Training, Languages)

• Bachelor's or Master's degree in Computer Science, Computer Engineering, Information Technology, or a related field.
• Expert‑level proficiency in SQL and Python; strong knowledge of Spark, Scala, or Java
• Deep experience with cloud data platforms (AWS, GCP, or Azure) and associated managed services
• Proven ability to design and implement complex data models across relational, NoSQL, and lakehouse architectures
• Advanced knowledge of data orchestration tools (e.g., Apache Airflow, Prefect, dbt) and CI/CD for data pipelines
• Strong understanding of data governance, data quality frameworks, and metadata management
• Familiarity with MLOps patterns and infrastructure requirements for machine learning workloads
• Ability to communicate complex technical concepts clearly to non‑technical stakeholders and senior leadership
• Demonstrated leadership in building and mentoring engineering teams
• Strong commercial awareness and ability to make pragmatic engineering trade‑offs aligned with business value
• Fluent in English; proficiency in Hindi is an advantage

Work Experience

• With 8-10 years of progressive experience in data engineering, with at least 2 years in a technical lead or senior engineering role.
• Demonstrated track record of delivering large-scale data infrastructure in a cloud environment. ITIL Certification is an advantage but not mandatory
• Experience with real-time and streaming data platforms (e.g., Apache Kafka, Flink, Kinesis)