Data Lead (Life Sciences)

In the last year at Loka, our engineering teams have helped clients advance the world’s #1 AI reading tutor, eliminate $1B in food waste and develop novel drugs for fighting cancer. To cap it off, at the end of 2024 Loka was recognized by AWS as Innovation Partner of the Year, outshining 150,000 partners for the title. 

And we did it all while enjoying every other Friday off 😎 

As a Data Lead in Life Sciences, you will design and build modern cloud-data platforms for Life Sciences customers, focusing on Omics and analytics-heavy use cases. You will lead technical projects end to end, partner closely with Bioinformatics, ML and Product teams and ensure data infrastructure is scalable, reliable, secure and user friendly.

Join our team to feed your desire to grow, build with the latest tools and collaborate on projects you can be proud of.

• Design and implement scalable, cloud-native data platforms and applications for Life Sciences businesses, focusing on Omics and related multimodal datasets.
• Lead technical projects through architecture, design, implementation and rollout, setting standards and best practices for the team.
• Collaborate with Machine Learning, Data Science, Bioinformatics, Software Engineering, Design and Business teams to understand requirements and triage data or ETL issues.
• Define and implement data quality checks, tests and monitoring to maintain high standards of code, schema and data integrity.
• Monitor and analyze data flowing through pipelines and platforms, building appropriate dashboards, alerts and observability tooling.
• Manage a team of data engineers and assist them with project guidance and career development. 

• 5+ years of experience, including responsibility for production systems, in Data Engineering or a closely related role
• 3+ years of experience leading teams, including technical mentorship and delivery ownership
• Proven ability to communicate technical status, risks and trade-offs to clients and internal stakeholders, providing clear guidance on data platform and architecture decisions
• Advanced proficiency in Python and SQL for building data pipelines, transformations and analytics tooling
• Strong experience in ETL/ELT design, implementation and maintenance across batch and/or streaming workloads
• Hands-on experience with at least one major cloud provider (AWS, GCP or Azure) delivering data-centric products or platforms
• Experience with in-memory and disk-based data stores, relational and non-relational databases and search technologies (e.g. MySQL/PostgreSQL, MongoDB, DynamoDB, OpenSearch/Elasticsearch), with bonus points for graph databases (e.g. Neo4j)
• Experience with data warehousing concepts, dimensional/columnar modeling and modern warehouse/lakehouse patterns
• Working knowledge of data lakes, data warehouses and massively parallel processing (MPP) technologies or services
• Solid problem-solving skills and the ability to work through ambiguity, incomplete specifications and evolving requirements
• Experience collaborating with Bioinformatics teams or developing workflows and platforms that support Bioinformatics pipelines

• Working knowledge of core security and reliability concepts: IAM, federated authentication, SSO/SAML, encryption, network/security best practices, backup and disaster recovery
• Familiarity with Omics and Life Sciences datasets (e.g. RNA‑seq, ATAC‑seq, WGS) and relevant bioinformatics data formats (e.g. FASTQ, BAM, VCF, h5ad) 
• Strong experience with distributed systems for large-scale data processing and analytics
• Experience with Spark for large-scale and interactive data manipulation
• Experience with open table/lakehouse formats (e.g. Apache Hudi, Delta Lake, Apache Iceberg, Databricks) and their role in modern data platforms
• Experience with Infrastructure as Code (e.g. Terraform, CloudFormation) and CI/CD pipelines for data and infrastructure changes
• Experience with BI and data visualization tools (e.g. QuickSight, Looker, Tableau) for building dashboards and monitoring

• Curious: You want to learn and grow in different industries utilizing a modern tech stack.
• Autonomous: You thrive in a fully remote environment. 
• Collaborative: You enjoy working as part of a team. 
• Adaptable: You operate with a startup mindset and move at a startup pace.
• Dependable: You can be trusted to deliver high-quality work.