Data Engineering Talent Pipeline: Ingest, Build, Insight

Data Science Careers; København; On-site; DKK 600,000 - 900,000; Full time

Job summary

A prominent data engineering firm in Copenhagen is seeking a skilled Data Engineer to design and develop data handling systems. The ideal candidate will excel in building data ingestion pipelines, transforming data for analysis, and optimizing performance in cloud environments. Strong proficiency in programming languages such as Python and SQL, as well as familiarity with ETL tools like Apache Airflow, is required. This is a great opportunity to contribute to data-driven projects in a collaborative environment.

Qualifications

• Proficiency in programming languages like Python, Java, Scala, or SQL.
• Familiarity with ETL tools such as Apache NiFi, Apache Airflow, and Talend.
• Knowledge of databases (SQL and NoSQL) and data warehouses like Amazon Redshift and Snowflake.
• Understanding of big data frameworks such as Apache Hadoop, Apache Spark, and Apache Kafka.
• Experience with cloud platforms like AWS, Azure, or Google Cloud.

Responsibilities

• Build data pipelines to ingest data from various sources.
• Clean, transform, and structure raw data for analysis.
• Select and manage appropriate storage solutions.
• Design and implement data processing pipelines.
• Create data models and schemas for data analysts and scientists.

Skills

Python

Java

Scala

SQL

Apache NiFi

Apache Airflow

Talend

Informatica

Amazon Redshift

Snowflake

Hadoop

AWS S3

Apache Spark

Apache Kafka

Git

Job description

A prominent data engineering firm in Copenhagen is seeking a skilled Data Engineer to design and develop data handling systems. The ideal candidate will excel in building data ingestion pipelines, transforming data for analysis, and optimizing performance in cloud environments. Strong proficiency in programming languages such as Python and SQL, as well as familiarity with ETL tools like Apache Airflow, is required. This is a great opportunity to contribute to data-driven projects in a collaborative environment.