We are looking for a Senior Data Engineer to join our Data Engineering Team and take ownership of high-impact, greenfield data initiatives. You will work on building modern cloud-native data platforms, migrating on-premises legacy systems to the cloud, and laying the architectural foundation for AI-ready data infrastructure.
In this role, you will collaborate closely with Machine Learning, Data Science, and Product teams, serving as a key technical contributor and thought leader. You will also drive R&D efforts around agentic AI architectures, event-driven systems, and LLM-ready data pipelines – turning architectural concepts into production-grade solutions.
Job Description- Design and build scalable cloud-native data platforms from greenfield to production
- Design and implement near-real-time ingestion pipelines using event-driven patterns
- Define and enforce data platform standards including Data Lake and Lakehouse principles, medallion architecture, and data contracts
- Refactor, optimize, and modernize Spark and PySpark scripts for performance and maintainability
- Introduce best practices for code quality, testing, and CI/CD across data pipelines
- Drive adoption of AI tooling and agentic workflows within the Data Engineering team
- Ensure data quality, observability, scalability, and reliability across all platforms and pipelines
- Design and deliver self-service tooling and microservices that simplify platform usage
- Collaborate with cross-functional stakeholders including Product, Machine Learning, and Data Science teams
- Contribute to architecture decisions and technical R&D initiatives
- 5+ years of professional experience in Data Engineering
- Strong Python and SQL development skills
- Hands-on experience with Apache Spark and PySpark including query optimization and performance tuning
- Experience working with Databricks or Snowflake
- Practical experience with at least one major cloud provider such as Azure, AWS, or GCP
- Experience with stream processing technologies including Kafka or Spark Structured Streaming
- Strong understanding of ETL/ELT patterns, data modelling, and data warehousing concepts
- Experience with orchestration tools such as Apache Airflow or Azure Data Factory
- Knowledge of Infrastructure as Code tools including Terraform
- Understanding of production-grade systems including observability, scalability, reliability, and performance
- Ability to independently lead technical initiatives from concept to delivery
- Strong communication and collaboration skills
- Upper-Intermediate or higher English level
WILL BE A PLUS
- Familiarity with RAG pipeline design and LLM integration patterns
- Knowledge of data governance frameworks and tools such as Unity Catalog or Apache Atlas
- Experience with dbt for data transformation and modelling
- Familiarity with MLflow, Feature Stores, or ML platform integrations
PERSONAL PROFILE
- Proactive and self-driven mindset
- Strong analytical and architectural thinking
- Ability to work independently and take ownership of technical decisions
- Passion for innovation and modern engineering practices
- Knowledge-sharing and team-oriented approach
- Strong problem-solving skills
Skills Required
- 5+ years of professional experience in Data Engineering
- Strong Python and SQL development skills
- Hands-on experience with Apache Spark and PySpark, including query optimization and performance tuning
- Experience with Databricks or Snowflake
- Practical experience with at least one major cloud provider, such as Azure, AWS, or GCP
- Experience with stream processing technologies, including Kafka or Spark Structured Streaming
- Strong understanding of ETL/ELT patterns, data modeling, and data warehousing concepts
- Experience with orchestration tools such as Apache Airflow or Azure Data Factory
- Knowledge of Infrastructure as Code tools, including Terraform
- Understanding of production-grade systems, including observability, scalability, reliability, and performance
- Ability to independently lead technical initiatives from concept to delivery
- Strong communication and collaboration skills
- Upper-Intermediate or higher English level
- Familiarity with RAG pipeline design and LLM integration patterns
- Knowledge of data governance frameworks and tools such as Unity Catalog or Apache Atlas
- Experience with dbt for data transformation and modeling
- Familiarity with MLflow, Feature Stores, or ML platform integrations
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
