Data Tech Lead

Main Purpose of Job

This is a senior hands-on data engineering role supporting the delivery, maintenance, and improvement of our client's data platform and data warehouse services.
The role combines hands on development with technical oversight of distributed delivery teams. It is responsible for designing and maintaining reliable data pipelines, ETL processes, data models, APIs, and supporting AWS based services, while ensuring delivery aligns with development standards, architecture principles, and operational expectations.
The role will work across technologies including AWS S3, AWS Lambda, AWS Fargate, AWS Glue, Amazon Redshift, SQL, and Python. It will also provide day to day technical guidance and review for offshore development teams, helping ensure that work is correctly understood, appropriately designed, well implemented, tested, and suitable for long term support.

Key Accountabilities

Technical Delivery and Engineering Standards 
•     Take responsibility for the technical quality of delivered data engineering work, including design, implementation, code review, testing, documentation, and operational readiness.
•     Provide technical oversight of offshore development activity, ensuring work is correctly understood, appropriately designed, reviewed, tested, and delivered to the required engineering standard.
•     Apply development standards and architecture principles to data engineering and data warehouse development.
•     Contribute to technical design decisions, implementation approaches, and solution options.
•     Identify risks, gaps, or weaknesses in proposed technical approaches and raise them early.
•     Challenge proposed designs and implementations where they create risk around maintainability, performance, data quality, security, or supportability.
•     Support continuous improvement across data engineering practice, delivery quality, and operational reliability.

Data Architecture and Design
•     Support the design and evolution of data warehouse architecture and data models.
•     Work with technical leads, architects, and stakeholders to understand data requirements and translate them into maintainable technical solutions.
•     Ensure data structures are designed with clarity, performance, scalability, and long-term maintainability in mind.                                                                                                                                                                                                                              •    Support appropriate separation between raw, transformed, and reporting ready data where applicable.
•     Contribute to decisions around data modelling, data lineage, data quality, and data governance.
•     Maintain awareness of downstream reporting, analytics, and operational use cases when designing data solutions.

Working with Distributed Teams
•     Provide day to day technical guidance to near shore and offshore development teams working on data engineering and data warehouse delivery.
•     Review work delivered by distributed teams and challenge implementation where required.
•     Communicate clearly around development expectations, architecture, maintainability, testing, performance, and operational support.
•     Help ensure external or distributed teams are aligned with standards and delivery expectations.
•     Support planning, refinement, and prioritization of data engineering work where required.

Team Contribution
•     Work collaboratively with internal stakeholders, development teams, data teams, product owners, and third-party partners.
•     Maintain technical documentation for data warehouse processes, data models, technical decisions, and owned areas of implementation.
•     Share knowledge with other developers and help improve data engineering capability across the team.
•     Support handover and knowledge transfer from external or temporary resources into internal teams.
•     Undertake other projects, requests or duties as assigned from time to time by the Development Lead.

Data Engineering and Data Platform Development
•    Develop and maintain data pipelines, ETL processes, data models, APIs, and supporting data platform services.
•    Work with AWS based data services including S3, Lambda, Fargate, Glue, and Redshift where required.
•    Write, optimize, and maintain SQL used for data modelling, transformation, reporting, reconciliation, and validation.
•    Write and maintain Python based data engineering logic, scripts, jobs, and supporting services.
•    Support the design and implementation of reliable data ingestion, transformation, and delivery processes.
•    Build and maintain data structures that support reporting, analytics, operational insight, and business decision making.
•    Investigate and resolve defects, data quality issues, performance issues, and production support queries.

Data Quality and Operational Reliability
•     Design and maintain validation, reconciliation, and data quality checks to ensure data outputs are accurate, complete, and trusted.                                                                                                                                                                                                •     Support production reliability of data pipelines and services through appropriate logging, monitoring, alerting, failure handling, retry behavior, and incident investigation.
•     Help ensure data jobs and services are observable, supportable, and safe to operate in production.
•     Investigate failed or degraded data processes and support root cause analysis.
•     Document known failure modes, support processes, and operational considerations.

Knowledge, Skills and Experience

Essential Knowledge

• Proven experience as a Senior Data Engineer, Data Warehouse Developer, Data Engineer, or similar technical data role.
• Experience developing and maintaining data warehouse solutions and ETL processes.
• Strong understanding of data modelling, data transformation, and data quality principles.
• Experience working with cloud based data engineering services.
• Strong understanding of software engineering good practice, including maintainability, version control, testing, review, and documentation.
• Experience working in Agile delivery environments.
• Experience working with distributed, offshore, near shore, or third party development teams.
• Ability to provide technical guidance and challenge implementation decisions constructively.
• Ability to challenge proposed designs and implementations where they create risk around maintainability, performance, data quality, security, or supportability.
• Effective communication skills, with the ability to work with both technical and non technical stakeholders.
• Familiarity with Jira and Confluence for project and delivery management.

Essential Functional / Technical Skills

• Strong SQL skills, including query optimization, data transformation, modelling, reconciliation, and validation.
• Strong Python skills for data engineering, automation, ETL, or API development.
• Experience with AWS S3 for data storage and data exchange.
• Experience with AWS Glue or similar ETL tooling.
• Experience with Amazon Redshift or similar cloud data warehouse technology.
• Experience with AWS Lambda, AWS Fargate, or similar serverless/container-based services.
• Experience developing, supporting, or integrating APIs used by data platforms or downstream systems.
• Experience with data quality checks, validation, reconciliation, and production support of data pipelines.
• Familiarity with GitHub or similar version control tools.
• Understanding of CI/CD, environment management, deployment safety, and operational support.

Desirable

• Experience providing technical oversight to offshore or near shore delivery teams.
• Experience with infrastructure as code tools such as Terraform.
• Experience with Java or other backend development languages.
• Familiarity with AWS IAM, secrets management, access control, and cloud security fundamentals.
• Experience with data governance, data lineage, and data catalogue tooling.
• Experience with reporting, BI, or analytics platforms.
• Experience working in high traffic, consumer, ecommerce, media, sport, or membership-based organizations.

What we offer:

•     Dynamic and supporting international teams.
•     Regular assessments and performance reviews. You will have the opportunity for promotion, bonuses and a raise in accordance with the pace at which you develop and your performances.
•     Hybrid or office work.
•     20-25 vacation days per year.
•     4 days of sick leave (100% paid)
•     Equipment for work, laptop and all necessary additions.
•     Access to trainings and courses.
•     Private health insurance.
•     FIT Pass card for many sports’ facilities

Provides digital transformation, software engineering, and cloud services.