Data Lead (Life Sciences)
New
L
Loka® IncLife Sciences
LatAmFull-TimeLead
Salary not disclosed
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Job Details
- Languages
- English
- Experience
- 5+ years of experience, including responsibility for production systems, in Data Engineering or a closely related role; 3+ years of experience leading teams
- Required Skills
- PythonSQLCloud ComputingData engineeringData modelingDistributed Systems
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
- 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)
- Experience with in-memory and disk-based data stores, relational and non-relational databases and search technologies
- 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
- Experience collaborating with Bioinformatics teams or developing workflows and platforms that support Bioinformatics pipelines
Responsibilities
- 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.
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