Senior Data Engineer

• Practice Data

• Technologies Business Intelligence Jobs and Data Recruitment

• Location Toronto, Canada

• Type Permanent

A Series A Business  are accelerating the world’s ability to discover, learn, and communicate science faster through visuals. Today, they empower millions of scientists to create beautiful, accurate biological figures for communication within pharma companies and academic research. As AI automates large parts of research, they will transform complex data, experimental results, and text inputs into clear, intuitive visuals that scientists, decision-makers, and broader audiences can quickly interpret. Visual communication will be critical to accelerating breakthroughs across academia and industry, and the idea is that they will bridge the gap between specialized knowledge domains

Our Data Platform team is at the heart of collecting and unlocking data. We seek to build and maintain the right architecture and tooling to support our data science, analytics, product, and machine learning initiatives. An ideal candidate will have plenty of experience building data products and helping shape data strategy in a fast-paced startup environment

What you'll bring : 7+ years of data engineering experience of relevant industry experience Expertise working with Data Warehousing platforms (AWS RedShift or Snowflake preferred) and data lake / lakehouse architectures Experience with Data Streaming platforms (AWS Kinesis / Firehose preferred) Demonstrated ability to (creatively) solve complex architectural problems, think about tradeoffs and systems design Effective communication skills and ability to translate deeply technical designs into business appropriate representations as well as analyze business needs and requirements ensuring implementation of data services directly correlates to the strategy and growth of the business

Expertise with SQL and programming languages commonly used in data platforms (Python, Spark, etc) Experience with data pipeline orchestration (e.g., Airflow) and data pipeline integrations (e.g. Airbyte, Stitch)

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