We are looking for a Data Engineer to help design and build scalable data platforms that support analytics, reporting, and data-driven decision-making across the organization. In this role, you will develop robust data pipelines, contribute to the evolution of our cloud data platform, and ensure reliable and efficient data processing across multiple projects and teams.
Job Description
Responsibilities
- Design and develop scalable and reliable data platforms and/or data pipelines for analytical and operational use cases
- Design and implement data processing workflows using distributed processing frameworks such as Apache Spark/pySpark (Databricks)
- Contribute to the evolution of the organization’s cloud data platform using Azure technologies (e.g., Azure Data Factory, Synapse, Microsoft Fabrik, Databricks, Event Hub, Azure Data Lake Storage)
- Strong background in data modelling to support analytics, reporting, and downstream data consumption
- Integrate and process data from multiple internal and external sources while ensuring data consistency, quality, and reliability
- Take ownership of data pipeline reliability, monitoring, and performance, ensuring scalable and maintainable data processing workflows
- Collaborate with data analysts, data scientists, and engineering teams to translate business and analytical requirements into robust data solutions
- Drive improvements in data engineering practices, including pipeline design standards, testing approaches, and operational reliability
- Participate in evaluating and introducing new tools and technologies within the data engineering ecosystem
Required Qualifications
- Strong hands-on experience (4+ years) in data engineering or building data processing platforms
- Strong SQL skills and solid experience with Python for building and maintaining data pipelines
- Experience working with distributed data processing frameworks such as Apache Spark/pySpark (Databricks experience is a strong advantage)
- Practical experience designing and implementing data pipelines in cloud environments, preferably within the Azure ecosystem
- Experience designing data pipelines and data models for production-scale analytical systems
- Strong understanding of data engineering concepts including ETL/ELT design, dimensional modeling, and data warehousing principles
- Experience working with modern data lake architectures and data formats such as Parquet and JSON
- Experience with workflow orchestration tools (e.g., Airflow)
- Experience with database development and performance optimization
- Ability to design scalable and maintainable data solutions with minimal supervision
- Strong collaboration and communication skills
- Professional working proficiency in English
Nice to Have
- Experience with modern cloud data warehouses such as Snowflake, BigQuery, or Redshift
- Experience with streaming data technologies (e.g., Event Hub, Kafka, Spark Streaming)
- Experience with Delta Lake or other lakehouse technologies
- Familiarity with CI/CD practices and Git-based development workflows
- Experience working in agile development environments
Skills Required
- 4+ years of experience in data engineering or building data processing platforms
- Strong SQL skills
- Solid experience with Python for building and maintaining data pipelines
- Experience with Apache Spark or PySpark; Databricks experience is advantageous
- Experience designing and implementing cloud data pipelines, preferably in Azure
- Experience designing data pipelines and data models for production-scale analytical systems
- Understanding of ETL/ELT design, dimensional modeling, and data warehousing principles
- Experience with modern data lake architectures and Parquet or JSON data formats
- Experience with workflow orchestration tools such as Airflow
- Experience with database development and performance optimization
- Ability to design scalable and maintainable data solutions with minimal supervision
- Strong collaboration and communication skills
- Professional working proficiency in English
- Experience with Snowflake, BigQuery, or Redshift
- Experience with streaming technologies such as Event Hub, Kafka, or Spark Streaming
- Experience with Delta Lake or other lakehouse technologies
- Familiarity with CI/CD and Git-based development workflows
- Experience working in agile development environments
What We Do
Sigma Software Group, an award-winning and trusted IT partner, has been serving customers for over 21 years, providing comprehensive IT solutions to various businesses, ranging from startups to established software product houses. As one of Europe's substantial IT consultancies, it brings together a dedicated workforce of over 2,100 professionals in 40 offices across 19 countries. With a diverse client base, including more than 300 enterprises, including Fortune 500 stalwarts, Sigma Software Group is a preferred choice for developing solutions that help businesses create cutting-edge products while meeting their unique needs. Sigma Software Group operates as a dynamic ecosystem of tech companies, offering 25 ready-to-implement innovative products and 40+ value-added services. Furthermore, Sigma Software Group is committed to fostering innovation through initiatives such as the Sigma Software Labs business incubator, Sigma Software University, the SID Venture Partners VC Fund, UA Tech Network, Techosystem, the European Business Association, and other collaborative efforts. Since 2015, Sigma Software Group has consistently earned recognition on the IAOP's prestigious World's Top 100 Outsourcing list. The company's accomplishments have also been acknowledged by prominent global media outlets such as Forbes, CNBC, The Times, and Reuters
