S4 - Data BAU Lead

Responsibilities

We are looking for a seasoned BAU Lead - Data Engineering to lead our data operations and support function in a cloud-first environment. The ideal candidate will bring strong technical leadership, hands-on expertise in AWS and Snowflake, and proven experience in managing Business-As-Usual (BAU) data platforms, production support, and continuous improvement initiatives.

• Develop tools to improve data flows between internal/external systems and the data lake/warehouse.

• Work with stakeholders to understand needs for data structure, availability, scalability, and accessibility.

• Build robust and reproducible data ingest pipelines to collect, clean, harmonize, merge, and consolidate data sources.

• Understanding existing data applications and infrastructure architecture.

• Build and support new data feeds for various Data Management layers and Data Lakes.

• Evaluate business needs and requirements.

• Support migration of existing data transformation jobs in Oracle, and MS-SQL to Snowflake.

• Lead the migration of the existing data transformation jobs in Oracle, Hive, Impala etc. into Spark, Python on Glue etc.

• Able to document the processes and steps.

• Develop and maintain datasets.

• Improve data quality and efficiency.

• Lead Business requirements and deliver accordingly.

• Collaborate with Data Scientists, Architect and Team on several Data Analytics projects.

• Collaborate with DevOps Engineer to improve system deployment and monitoring process.

• Experience in critical production support and how the BAU functions is preferred.

Requirements

Key Skills

• Lead a team of data engineers in managing day-to-day BAU operations, production support, incident management, and platform stability.

• Strong AWS knowledge in terms of designing new architecture and providing optimized solutions for existing ones. (S3, Glue, DMS, MWAA, AMS, IAM).

• In-depth knowledge with respect to Snowflake and its architecture.

• Prefer prior Experience in BAU environment.

• Good knowledge on Airflow and MWAA.

• Hands-on experience in SQL/Python/Pyspark.

• Expertise in optimizing techniques in cloud environments.

• Should have the vision on data strategy and able to deliver the same.

• Should be able to lead the design and implementation of data management processes, including data sourcing, integration, and transformation.

• Able to manage and lead a team of data professionals, providing guidance, mentoring and foster a collaborative and innovative team culture focused on continuous improvement.

• To evaluate and recommend data-related technologies, tools, and platforms.

• Collaborate with IT teams to ensure seamless integration of data solutions.

• Should have experience in Implementing and enforcing data security protocols and ensure compliance with relevant regulations.

Required Qualifications

• At least 8+ years of Data Engineer Experience.

• Bachelor qualification in a computer science or STEM (science, technology, engineering, or mathematics) related field.

• At least 5+ years of recent hands-on professional experience (actively coding) working as a Lead handling support & production issue.

• 2+ experience with large scale datasets, data lake and data warehouse technologies such as AWS Redshift, Google BigQuery, Snowflake. Snowflake is highly preferred.

• At least 3+ years of experience in ETL (AWS Glue), Amazon S3, Amazon RDS, Amazon Kinesis, Amazon Lambda, Apache Airflows, Amazon Step Functions.

• Professional experience working in an agile, dynamic and customer-facing environment is required.

• Understanding of distributed systems and cloud technologies (AWS) is highly preferred.

• Understanding of data streaming and scalable data processing is preferred to have.

• Strong knowledge in scripting languages like SQL, Python, UNIX shell and Spark is required.

• Understanding of RDBMS, Data ingestions, Data flows, Data Integrations etc.

• Technical expertise with data models, data mining and segmentation techniques.

• Experience with full SDLC lifecycle and Lean or Agile development methodologies.

• Knowledge of CI/CD and GIT Deployments.

• Ability to work in team in diverse/multiple stakeholder environment.

• Ability to communicate complex technology solutions to diverse teams namely, technical, business and management teams.

Soft Skills

• Ability to work in a collaborative environment and coach other team members on coding practices, design principles, and implementation patterns that lead to high quality maintainable solutions.

• Excellent communications and stake-holder management are required.

• Ability to handle senior leadership and report to them if required.

• Ability to work in a dynamic, agile environment within a geographically distributed team.

• Ability to focus on promptly addressing customer needs.

• Ability to work within a diverse and inclusive team.

• Technically curious, self-motivated, versatile and solution-oriented.