Data Architect/Scientific Data Engineer

Engender Technologies
Full-time
On-site

Engender Technologies is at the forefront of innovation, transforming the dairy industry with our groundbreaking gender selection technology. We are looking for a skilled and motivated Data Architect to join our dynamic team. In this role, you will play a crucial part in shaping our data strategy and architecture, ensuring data integrity and availability to support our innovative solutions.

Key Responsibilities:

  • Designing data models and schemas for structured and unstructured data (e.g. biological samples, events, results, metadata).
  • Planning and building ETL/ELT pipelines (Extract, Transform, Load) from hardware, software logs, user input, and external systems.
  • Discovery and gathering requirements to procure a LIMS integration, either by adapting a commercial system or helping build/customise an internal one and then leading the implementation of this system.
  • Defining and maintaining data standards, naming conventions, lineage tracking, and governance policies.
  • Ensuring data integrity, auditability, and regulatory compliance (if applicable).
  • Supporting analytics and reporting, and eventually enabling machine learning or statistical modelling.
  • Making technical decisions about storage layers (SQL/NoSQL, cloud/on-prem, etc.), metadata strategies, and APIs.
  • Design and implement robust data architectures, ensuring they are scalable and maintainable.
  • Collaborate with cross-functional teams to define data requirements and ensure data solutions align with business objectives.

Requirements

What We're Looking For:

  • Bachelor's degree in Computer Science, Information Systems, or a related field; Master’s degree is a plus.
  • Strong communication and collaboration skills to work effectively with stakeholders across the organization
  • 7+ years of experience in data architecture, data modeling, and database design.
    • Data Modeling  - Conceptual, logical, and physical data models; normalization/denormalization; temporal modelling
    • Databases - NoSQL (MongoDB, Redis, CSV), time series DBs (csv files, InfluxDB), and some SQL
    • Infrastructure - Data lake architecture, cloud platforms (AWS/GCP/Azure), Docker/Kubernetes (nice to have)
    • Data Quality & Governance - Data validation, audit trails, versioned data, compliance (GDPR, 21 CFR Part 11 if relevant)
    • Data Warehousing - e.g. Snowflake, BigQuery, Redshift, or custom analytical warehouses (nice to have)
  • ETL/ELT - Tools like Apache Airflow, dbt, Fivetran, custom Python pipelines 
  • Able to implement the architecture (via programming in Python or C# etc.) is required
  • LIMS Integration - Understanding of commercial LIMS (e.g. Infor M3, LabWare, Benchling) or experience designing custom solutions
  • APIs & Interoperability - RESTful APIs. Bonus if GraphQL, message buses (e.g., MQTT, Kafka)
  • Programming - Python, SQL, some Bash or PowerShell scripting; bonus if experience with C# or C/C++, R, etc

Bonus Points:

  • Experience in the agricultural or biotechnology sectors.
  • Knowledge of machine learning and data analytics.

Benefits

  • The opportunity to be at the forefront of a revolutionary technology in the dairy industry.
  • A collaborative and dynamic work environment with a passionate team.
  • Competitive salary 
  • Health Benefits 
  • The chance to make a real impact on the future of animal agriculture