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Diageo
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Senior Manager - Data Engineering Lead

Senior Manager - Data Engineering Lead

Diageo

14 - 19 years

22 - 27 Lacs

bengaluru

Posted:3 hours ago| Platform:

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Skills Required

data engineering airflow bigquery kafka redshift apache spark sql synapse glue dbt snowflake databricks python

Work Mode

Work from Office

Job Type

Full Time

Job Description

About the role:

Data Management roles are skills and expertise in the secure storage and management of data in compliance with guidelines, standards and best practice
They enable efficient and high quality data analysis by designing and implementing approaches to clean and transform data and store data in the most appropriate way

Purpose of Position:

We are seeking a highly skilled and experienced Data Engineering Lead to spearhead our data architecture strategy, oversee robust data engineering initiatives, and manage data lake operations
The ideal candidate will be a hands-on leader with deep expertise in building and optimizing data platforms that support advanced analytics and business intelligence at scale

Qualification: Bachelors or Masters 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, BigQuery, 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.

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