Senior Manager - Data Engineering Lead

Job Title : Senior Manager - Data Engineering Lead

Qualification : Bachelor’s or master’s degree in computer science, Data Engineering, or related field.

Required skillset :

Experience in data engineering.

Proven experience in cloud platforms (AWS, Azure, or GCP) and data services (Glue, Synapse, Big Query, Databricks, etc.).

Hands-on experience with tools like Apache Spark, Kafka, Airflow, dbt, and modern orchestration platforms.

Technical Skills

Proficient in SQL, Python / Scala / Java.

Strong understanding of modern data Lake concepts (e.g., Snowflake, Redshift, BigQuery).

Familiarity with CI / CD, Infrastructure as Code (e.g., Terraform), and DevOps for data.

Nice to Have :

Prior experience working in a regulated industry (alcohol, pharma, tobacco, etc.).

Exposure to demand forecasting, route-to-market analytics, or distributor performance management.

Knowledge of CRM, ERP, or supply chain systems (e.g., Salesforce, SAP, Oracle).

Familiarity with marketing attribution models and campaign performance tracking.

Preferred Attributes :

Strong analytical and problem-solving skills.

Excellent communication and stakeholder engagement abilities.

Passion for data-driven innovation and delivering business impact.

Certification in cloud platforms or data engineering (e.g., Google Cloud Professional Data Engineer).

Excellent communication and stakeholder management skills.

Key Accountabilities :

Design and implement scalable, high-performance data architecture solutions aligned with enterprise strategy.

Define standards and best practices for data modelling, metadata management, and data governance.

Collaborate with business stakeholders, data scientists, and application architects to align data infrastructure with business needs.

Guide the selection of technologies, including cloud-native and hybrid data architecture patterns (e.g., Lambda / Kappa architectures).

Lead the development, deployment, and maintenance of end-to-end data pipelines using ETL / ELT frameworks.

Manage ingestion from structured and unstructured data sources (APIs, files, databases, streaming sources).

Optimize data workflows for performance, reliability, and cost efficiency.

Ensure data quality, lineage, cataloging, and security through automated validation and monitoring.

Oversee data lake design, implementation, and daily operations (e.g., Azure Data Lake, AWS S3, GCP BigLake).

Implement access controls, data lifecycle management, and partitioning strategies.

Monitor and manage performance, storage costs, and data availability in real time.

Ensure compliance with enterprise data policies and regulatory requirements (e.g., GDPR, CCPA).

Lead and mentor a team of data engineers and architects.

Establish a culture of continuous improvement, innovation, and operational excellence.

Work closely with IT, DevOps, and InfoSec teams to ensure secure and scalable infrastructure.

Flexible Working Statement : Flexibility is key to our success. From part-time and compressed hours to different locations, our people work flexibly in ways to suit them. Talk to us about what flexibility means to you so that you’re supported from day one.

Diversity statement : Our purpose is to celebrate life, every day, everywhere. And creating an inclusive culture, where everyone feels valued and that they can belong, is a crucial part of this.

We embrace diversity in the broadest possible sense. This means that you’ll be welcomed and celebrated for who you are just by being you. You’ll be part of and help build and champion an inclusive culture that celebrates people of different gender, ethnicity, ability, age, sexual orientation, social class, educational backgrounds, experiences, mindsets, and more.

Our ambition is to create the best performing, most trusted and respected consumer products companies in the world. Join us and help transform our business as we take our brands to the next level and build new ones as part of shaping the next generation of celebrations for consumers around the world.