Data Lead (Life Sciences)

External

Lokajobs · Latin America

Full-timeOn-site2d ago

ApacheAWSAzureCI/CDCloudFormationData Warehousing

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About the role

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.

Requirements

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

Preferred but Not Required

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

Personality Profile

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.

Data Lead (Life Sciences)

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