Data / ML Engineer

HCLTech; Göteborgs kommun; On-site; SEK 600,000 - 900,000; Full time

Job summary

HCLTech in Sweden seeks a Data / ML Engineer to design and scale production-grade data and ML pipelines across data engineering, feature stores, model lifecycle management and geospatial analytics. You will build Parquet and Delta Lake stores, and orchestrate workflows with Airflow/ADF to ensure reliable data processing.

Responsibilities include data validation, ML training and optimization at scale, experiment tracking, map-matching implementations, and deploying models for production.

Qualifications

• Experience in data engineering, feature stores, ML model lifecycle management, geospatial analytics, and cloud-based orchestration frameworks.
• Strong Python, SQL and PySpark skills for large-scale data processing.
• Familiarity with MLops, CI/CD pipelines, and production ML deployment.

Responsibilities

• Design, build, and industrialize scalable data and ML pipelines.
• Develop and manage feature stores using Parquet and Delta Lake.
• Implement workflow orchestration using Apache Airflow and/or Azure Data Factory (ADF).
• Build automated data validation and transformation testing frameworks.
• Train, evaluate, and optimize ML models at scale.
• Implement experiment tracking and model performance monitoring.
• Develop geospatial analytics and map-matching solutions for route reconstruction.
• Package and deploy ML models for production environments.
• Collaborate with data scientists, architects, and software teams to operationalize AI solutions.

Skills

ML Engineering

Airflow

Feature Store

Experiment Tracking

Python

SQL

PySpark

Data Quality

Geospatial Analytics

Route Reconstruction

Tools

Parquet

Delta Lake

Databricks

Azure

AWS

GCP

Airflow

ADF

Job description

We are seeking a skilled Data / ML Engineer to build and scale production-grade data and machine learning pipelines. The ideal candidate will have experience in data engineering, feature stores, ML model lifecycle management, geospatial analytics, and cloud-based orchestration frameworks.

Key Responsibilities

• Design, build, and industrialize scalable data and ML pipelines.
• Develop and manage feature stores using Parquet and Delta Lake.
• Implement workflow orchestration using Apache Airflow and/or Azure Data Factory (ADF).
• Build automated data validation and transformation testing frameworks.
• Train, evaluate, and optimize ML models at scale.
• Implement experiment tracking and model performance monitoring.
• Develop geospatial analytics and map-matching solutions for route reconstruction.
• Package and deploy ML models for production environments.
• Collaborate with data scientists, architects, and software teams to operationalize AI solutions.

Required Skills

• Machine Learning Engineering
• Apache Airflow / Azure Data Factory (ADF)
• Feature Store Design
• Experiment Tracking (MLflow or similar)
• Python, SQL, PySpark
• Data Quality & Transformation Testing
• Geospatial Analytics
• Route Reconstruction & Map-Matching

Preferred Qualifications

• Experience with Databricks, Azure, AWS, or GCP.
• Knowledge of MLOps and CI/CD pipelines.
• Experience handling large-scale telemetry, vehicle, IoT, or sensor data.
• Exposure to Automotive, Mobility, GIS, or Logistics domains.