Lead Data Engineer (AWS) | Hybrid (4x WFH; 1x RTO)

About the Role

We are seeking a highly experienced Lead Data Engineer (AWS) to join a growing enterprise technology team. This is a senior, hands‑on leadership role responsible for designing, building, modernising, and operating enterprise‑scale data platforms on AWS while providing technical leadership and mentorship to a team of engineers.

This position is ideal for someone who enjoys remaining deeply involved in technical delivery while driving engineering standards, solution design, and platform modernisation initiatives.

Key Responsibilities

• Lead the design, development, and modernisation of enterprise data platforms on AWS.

• Architect and build scalable ETL/ELT, batch, and streaming data pipelines.

• Develop and maintain data lakes, lakehouses, data warehouses, and analytical data models.

• Provide technical leadership through solution design, architecture reviews, code reviews, and engineering best practices.

• Mentor and guide Data Engineers and technical team members.

• Implement and support data governance, security, monitoring, logging, and operational excellence initiatives.

• Drive CI/CD, Infrastructure as Code, automated testing, and platform reliability improvements.

• Collaborate with business stakeholders, architects, and executive leadership on strategic data initiatives.

• Troubleshoot production issues, perform root‑cause analysis, and optimise performance across data platforms.

Required Qualifications

• Minimum 10 years of progressive experience in Data Engineering, Data Integration, Data Warehousing, or Enterprise Data Platform delivery.

• At least 5 years of hands‑on AWS production experience designing and implementing enterprise data solutions.

• At least 3 years in a leadership capacity, such as Lead Data Engineer, Technical Lead, Solution Lead, or equivalent.

• Strong experience building enterprise‑scale:

  • ETL/ELT pipelines

  • Batch and streaming data solutions

  • Data lakes and lakehouses

  • Data warehouses and analytical platforms

• Advanced proficiency in:

  • Python

  • SQL

  • Git‑based development

  • CI/CD practices

  • Infrastructure as Code (Terraform or CloudFormation)

AWS Technologies

Strong experience with several of the following services:

• Amazon S3

• AWS Glue

• AWS Lambda

• AWS Step Functions

• AWS DMS

• Amazon EMR

• Amazon Athena

• Amazon Redshift

• Amazon RDS / Aurora

• AWS Lake Formation

• Glue Data Catalog

• Amazon MWAA (Airflow)

• Amazon MSK

• Amazon Kinesis

Additional Requirements

• Strong understanding of AWS security and governance, including IAM, KMS, Secrets Manager, role‑based access controls, metadata management, lineage, retention, and audit logging.

• Experience with data quality frameworks, reconciliation, monitoring, observability, incident management, and production support.

• Strong communication and stakeholder management skills.

• Ability to lead architecture discussions and provide technical direction across engineering teams.

Preferred Qualifications

Experience within highly regulated industries such as:

• Banking

• Financial Services

• FinTech

• Payments

• Remittance

• Lending

• Insurance

Experience with the following is highly advantageous:

• Medallion Architecture

• Kafka

• Change Data Capture (CDC)

• Enterprise Data Governance

• Business Intelligence & Analytics Platforms

• AI/ML Data Pipelines

Preferred AWS Certifications:

• AWS Certified Data Engineer

• AWS Certified Solutions Architect

• AWS Certified DevOps Engineer