Data Platform Engineer Specialist

Experteer Overview

You’ll mentor peers, drive best practices, and push for high performance, security, and governance in a data mesh environment. This role offers opportunities to influence large-scale data solutions and contribute to patient-focused outcomes.

• Collaborate with data engineers, scientists, and stakeholders to understand complex data needs in bioinformatics, omics, and clinical data
• Design, build, and maintain data infrastructure on AWS supporting a data mesh architecture
• Automate provisioning, scaling, and maintenance to boost efficiency, performance, scalability, and cost control
• Lead development and optimization of data pipelines (ETL/ELT) leveraging AWS and modern tooling
• Implement data monitoring and alerting; collaborate with DevOps to resolve data issues
• Ensure data security, compliance, and governance across the data platform
• Enforce global data engineering standards aligned with architecture, quality, and governance
• Demonstrate expertise in data warehouses, data lakes, and distributed processing (Spark, Hadoop, Kafka) in production environments
• Show advanced SQL proficiency (Snowflake preferred) and experience with relational and non-relational databases
• Master programming languages (Python, Shell, Scala/Java) for data engineering solutions
• Work in cross-functional agile teams to architect hybrid-cloud solutions and automated pipelines
• Document infrastructure design, configuration, and processes for reference and training
• Act as a mentor and leader to junior engineers; foster collaboration and growth
• Engage with the data engineering community by sharing insights and best practices

• Bachelor's/Master's in STEM or a related field with 4-6 years in data engineering
• Strong background in data and cloud solutions, pipelines, and service-oriented architectures
• Experience with data integration, ETL/ELT, and Data Mesh architectures
• Experience with multimodal data systems (batch, near real-time, streaming)
• Proven ability to design distributed architectures for large-scale processing (AWS, Snowflake, Spark, Hadoop, Kafka)
• Advanced SQL skills and experience with relational/non-relational databases
• Proficiency in Python, Shell, and Scala/Java
• Expertise in IaC and DataOps (Terraform, CI/CD, orchestration)
• Extensive experience with Agile
• Excellent communication and leadership abilities
• Curiosity and commitment to continuous learning

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