Data Foundation Engineering Lead - Evinova

Description

The company is building a platform-wide data foundation that supports its products, data science work and AI agents. This role leads that effort, which aims to deliver category-leading capabilities.

You will design, build and tune cloud data lakehouse infrastructure and operating frameworks that allow quick iteration and highly reliable systems. As one of the most senior engineers on the team, you will work hands-on, guide colleagues, mentor them, and share your knowledge of cloud data infrastructure, automation and best practice across the whole company.

Responsibilities

• Design and run AWS data services including Lake Formation, Glue (ETL, Data Catalog and Schema Registry), Athena, and either EMR or Redshift Serverless, understanding how they work together.
• Work with open table formats such as S3 Tables, Apache Iceberg (preferred) or Delta Lake, including partition and schema evolution, time travel and compaction, and knowing when each matters.
• Build production streaming pipelines on Kinesis Data Streams or MSK, handling exactly-once semantics, windowing, late-arriving data and backpressure.
• Define infrastructure in code using AWS CDK (TypeScript) or CloudFormation rather than the console. Build CI/CD for data pipelines with GitHub Actions and some Terraform.
• Design dimensional models, event schemas and slowly changing dimensions, weighing normalised against denormalised storage for each access pattern.
• Implement column-level security, row-level filtering or tag-based access control, with policy driven by data classification.
• Write ETL, feature extraction and data quality logic in Python or Spark, using PySpark or Spark Scala for distributed transforms.
• Mentor and guide junior and mid-level engineers, build a culture of learning and collaboration, and lead the adoption of tooling, patterns and automation practices.
• Work with product management, security and other teams to align the data foundation with business goals and keep development and operational workflows consistent.

Requirements

• 10+ years in data engineering roles, including substantial work on SaaS and multi-tenant data platforms.
• A proven record of mentoring team members on data platform projects.
• Strong understanding of AWS services including VPC, IAM, EC2, S3, RDS, Lambda, EKS, AWS WAF and AWS CloudTrail.
• Expert knowledge of S3, RDS, DynamoDB, Kinesis, Glue, DataZone, Athena, Redshift Serverless and AWS EventBridge.
• Deep proficiency in Docker, Kubernetes, Helm and the wider ecosystem of related tools.
• Expertise in CI/CD tools such as ArgoCD and GitHub Actions.
• Advanced experience with AWS CDK (TypeScript preferred) and CloudFormation.
• Good knowledge of IAM, AWS KMS, encryption standards, AWS WAF and security compliance frameworks including NIST.
• Good experience using OpenTelemetry, Prometheus, Grafana, AWS CloudWatch and AWS CloudTrail for monitoring and incident response.
• Extensive knowledge of AWS Glue, AWS Kinesis and Managed Kafka for real-time and batch data processing.
• Strong scripting and automation skills in TypeScript and Bash.
• Experience managing multiple AWS accounts with AWS Control Tower.
• Excellent verbal and written communication, with the ability to explain complex technical concepts to varied stakeholders.
• You can see the strategic direction and help shape smaller initiatives to fit it.
• You enjoy mentoring and building a collaborative, innovation-driven team culture.
• You can manage several priorities and stay effective in a fast-moving environment.
• You enjoy using technology to solve complex problems and improve efficiency.
• You build infrastructure that delivers measurable business and customer value.
• Desired: advanced expertise in AWS CDK, including building complex, reusable constructs and pipelines.
• Desired: experience with monitoring and logging tools such as Prometheus, Grafana and AWS CloudWatch.
• Desired: exposure to multi-tenant SaaS platforms and best practices.
• Desired: experience working with AI tools and frameworks, which is a plus.

Conditions

Office attendance averages at least three days per week, with some flexibility for individual circumstances.

Applications close on 17 December 2026. The role was posted on 29 October 2026.

The company welcomes applications from all qualified candidates and complies with laws on non-discrimination, work authorization and employment eligibility.