Data Engineer
Core
Design and implement modern, scalable data solutions and high-performance data architectures for clients in logistics and industrial processes.
Role type
Senior Data Engineer (Data Architecture & Engineering)
Builds
Scalable data architectures, data models, ETL pipelines, and integration solutions for legacy and modern data sources.
Domain
Logistics, Industrial Processes, Data Engineering
Deliverable
production ML models | product features | dashboards & analysis
Required skills
Python, PySpark, SQL, NoSQL, Big Data technologies (Spark, HDFS, Parquet), REST APIs, Public Cloud (AWS, Azure, GCP), Snowflake, CI/CD tools
Preferred skills
R, MLOps (MLFlow, Prefect, TFX), Graph Databases (Neo4j), GenAI, Palantir, Splunk, Cloudera
Technologies
Python, PySpark, R, SQL, NoSQL, Spark, HDFS, Parquet, AWS, Azure, GCP, Snowflake, Neo4j, MLFlow, Prefect, TFX, Palantir, Splunk, Cloudera, Jira, Git
Responsibilities
Design and implement data architecture for clients based on high performance data management technologies; Develop data model and efficient data architecture schemas from governance policies to business use case availability; Work on data engineering tasks including data ingestion, data quality, and ETL processes; Design integration with legacy data sources; Define standards and best practices for developing applications using new architectures; Build high-performance algorithms, prototypes, and proof of concepts.
Seniority
Senior, hands-on IC