S4 - Data BAU Lead

Visa Hunt; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

Visa Hunt is seeking a seasoned BAU Lead - Data Engineering to head our data operations in a cloud-first setup. You will guide production support, design scalable data pipelines, and drive data architecture improvements across AWS and Snowflake.

You will mentor a team of data engineers, ensure data quality and security, and collaborate with IT and analytics teams to deliver data-driven solutions. Strong coding and stakeholder communication are essential.

Qualifications

• Lead a team of data engineers in BAU operations and production support.
• Strong AWS design and optimization skills (S3, Glue, DMS, MWAA, IAM).
• Deep knowledge of Snowflake architecture and data management.
• Experience in BAU environments and production incident handling.
• Proficiency with Airflow and MWAA.
• Hands-on SQL/Python/PySpark experience in cloud data platforms.
• Knowledge of data security and regulatory compliance.

Responsibilities

• Lead day-to-day BAU data operations and incident management.
• Develop tools to improve data flows between systems and data lake/warehouse.
• Build robust data ingest pipelines for multiple sources.
• Document processes and maintain datasets.
• Collaborate with Data Scientists, Architects and DevOps on analytics projects.
• Support migration of transformation jobs to Snowflake, Glue and Spark on AWS.

Skills

Team leadership

AWS

Snowflake

Airflow/MWAA

SQL

Python/PySpark

Data architecture

Data governance

Data security

Cloud optimization

Data strategy

Education

Bachelor's degree in CS or STEM

Tools

AWS

Snowflake

Apache Airflow

Glue

Spark

Python

SQL

Job description

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.

Originally posted on Himalayas