Data Engineer

This is a fully remote position, open to applicants in Germany.

📋 Description

• Create scalable architectures for data management and processing.

• Oversee the gathering of data from various sources, including API, batch, event, or streaming.

• Establish procedures for data aggregation.

• Design and develop stages for data pre-processing and post-processing.

• Strategize and design frameworks for data governance, security, provenance, and the overall data lifecycle.

• Utilize top-notch cloud technologies to meet OLTP and OLAP business requirements.

• Incorporate machine learning models and analytics components into workflows, including MLOps.

• Collaborate closely with Data Science and Application Development teams within an agile development framework.

⛳️ Requirements

• B.Sc., B.Eng. or higher in Computer Science, Computer/Electronic/Systems Engineering, or related fields.

• Demonstrated experience as a Data Engineer.

• Proficient with structured, semi-structured, and unstructured data (e.g., Relational, JSON, Schema-less).

• Skilled in creating, cleaning, and curating datasets and databases such as MySQL, PostgreSQL, MongoDB, Redis, Bigtable, time-series databases, or similar.

• Experience with serverless/distributed processing, e.g., Multiprocessing, containers, lambda, or similar.

• Knowledgeable in scheduling workflows, e.g., DAGs with Apache Airflow.

• Well-versed in various ETL methodologies.

• Familiarity with classical and deep learning-based machine learning techniques (e.g., CNNs, DL Auto-encoders, etc.).

• Important knowledge and experience with relevant data, analytics, visualization, and machine learning languages and libraries (e.g., Julia/Python, Boto3/Apache Airflow, Parquet, SciPy/NumPy, Pandas/Matplotlib, Keras/TensorFlow, PyTorch, etc.).

• Experience in Model Deployment / MLOps is advantageous.

• Interest in edge-based inference is also valuable.

• Proficient with AWS (Fargate, RDS, EC2, SageMaker, Timestream, EMR, Kinesis, MWAA, etc.), Docker, IaC (Terraform), CI/CD, monitoring, and related tools.

• Experience with Time-Series Data is a plus.

• Ability to communicate effectively in an interdisciplinary environment (AI/ML, product management, regulatory, clinical).

• Practical experience with ETL, Data Pipelines, and Cloud Deployments.

• Background in designing and building data solutions while ensuring confidentiality, integrity, and availability.

• Strong engineering interest in machine learning and data science.

• Business proficient in English (both spoken and written).

🏝️ Benefits

• The position offers a competitive salary.

• Opportunity to be a key contributor in the future of healthcare.