Data Engineer

This is a remote position.

A Data Engineer is sought to join an expanding Digital Health Start-Up. If you are passionate about building and scaling world-class MedTech products, solving real-world problems and making a difference in patients’ lives this could be the role for you!

The role can be based in Munich or on a fully remote basis within Europe.

The successful candidate will work for a business committed to empowering people living with chronic conditions to manage their own health and lead a quality life by harnessing the power of IoT, sensor, and AI technologies to ensure they get access to the intervention and personalised care they need.

Key responsibilities

• Develop scalable data management and data processing architectures.
  
• Manage data acquisition from API, batch, event or streaming sources.
  
• Develop processes for data aggregation.
  
• Design and develop data pre- and post-processing stages.
  
• Plan and design for data governance, security, provenance and the over-all data lifecycle.
  
• Leverage best-in-class cloud technologies to cater for OLTP and OLAP business needs.
  
• Integrate ML models and Analytic components into the workflows (including MLOps).
  
• Work closely with Data Science and Application Development teams in an agile development process.
  

Requirements

• B.Sc., B.Eng. or higher in Computer Science, Computer / Electronic / Systems Engineering, or similar disciplines.
  
• Proven experience as a Data Engineer
  
• Experienced with structured, semi-structured and unstructured data (e.g., Relational, JSON, Schema-less).
  
• Experience with creating, cleaning and curating datasets and databases such as: MySQL, PostgreSQL, MongoDB, Redis, Bigtable, time-series databases or similar.
  
• Serverless/distributed processing experience, e.g., Multiprocessing, containers, lambda or similar.
  
• Know-how for scheduling workflows, e.g., DAGs with Apache Airflow.
  
• Accomplished and versed with various ETL approaches.
  
• Exposure to classical and deep learning-based ML methods (e.g., CNNs, DL Auto-encoders, etc.)
  
• Knowledge and experience of relevant data, analytics, visualization and ML languages and libraries is important (e.g., Julia/Python, Boto3/Apache Airflow, Parquet, SciPy/NumPy, Pandas/Matplotlib, Keras/TensorFlow, PyTorch, etc.).
  
• Experience with Model Deployment / ML Ops is desirable. Edge-based inference is also of interest.
  
• Experience with AWS (Fargate, RDS, EC2, SageMaker, Timestream, EMR, Kinesis, MWAA, etc.), Docker, IaC (Terraform), CI/CD, monitoring and related tooling.
  
• Experience with Time-Series Data is a bonus.
  
• Communicating effectively in an interdisciplinary environment (AI/ML, product management, regulatory, clinical).
  
• Have practical experience with ETL, Data Pipelines and Cloud Deployments.
  
• Experience in design and building data solutions while ensuring confidentiality, integrity, and availability.
  
• A strong engineering interest in ML and data science.
  
• Business proficient in English (spoken and written)
  

Benefits

The role offers a competitive salary and most importantly the chance to be a central player in the future of healthcare.