Senior Data Engineer with SAP BW and Snowflake, Retail Platform

Location: Almaty, Kazakhstan; Astana, Kazakhstan; Belgrade, Serbia; Cluj-Napoca, Romania; Dnipro, Ukraine; Kharkiv, Ukraine; Krakow, Poland; Kyiv, Ukraine; Larnaca, Cyprus; Lodz, Poland; Lublin, Poland; Lviv, Ukraine; Monterrey, Mexico; Montevideo, Uruguay; Odesa, Ukraine; Remote.AR, Remote.LATAM-country; Remote.BR, Brazil; Remote.BG, Bulgaria; Remote.CO, Colombia; Remote.GE, Georgia; Remote.KZ, Kazakhstan; Remote.PL, Poland; Riga, Latvia; Rosario, Remote.LATAM-country; Sofia, Bulgaria; Tbilisi, Georgia; Varna, Bulgaria; Warsaw, Poland; Wroclaw, Poland; Yerevan, Armenia We are looking for a very senior hands-on Data Engineer with strong SAP BW and Snowflake experience who has led engineering teams. About 70% of the engineering work is extracting data from SAP BW and integrating it into Snowflake. You will work side by side with a recently appointed Engineering Manager who comes from a non-engineering background, helping them build engineering leadership skills. Together you will grow the team toward independent, high-performing delivery: operating model, engineering practices, standards and delivery discipline. The goal is for the client's team to run independently within about a year. You will get there through coaching-by-doing and knowledge transfer rather than long-term vendor dependency. The client is headquartered in Southern California, USA. Working on site for the first 4–6 weeks is mandatory for this role, to build trust and work directly with the Engineering Manager and the team. After that, you will be on site a few days a week during the following weeks. A valid US visa, or the ability to obtain one quickly, is required. The project supports a large international consumer goods company that is scaling its Snowflake-based data platform. Selected datasets are moved from SAP BW into Snowflake one business case at a time. They feed data products for sales and distribution, retail and market analytics, and e-commerce. The platform is already critical to the business: hundreds of business users work every day with AI-powered analytics built on Snowflake Cortex and Streamlit. Design, build and run data pipelines from SAP BW into Snowflake, including full and delta loads Do hands-on engineering work while coaching the Engineering Manager and the team Help the Engineering Manager build engineering leadership skills: planning, code quality, technical decision-making, managing engineers and contractors Establish reusable ingestion, modeling and data quality patterns for the team Define and roll out engineering standards: code review, testing, CI/CD, documentation, delivery discipline Deliver data products for sales, distribution and retail analytics in close collaboration with business stakeholders Work with a distributed team of internal engineers and external contractors across time zones Reduce key-person dependency through knowledge transfer and pairing Help introduce AI-assisted and agentic engineering practices across the development lifecycle Work with the Lead Architect to keep delivery aligned with target architecture and governance 7+ years of hands on data engineering experience including lead roles Hands on experience extracting data from SAP BW into a cloud data warehouse Strong hands on experience with Snowflake including data loading performance cost awareness security and access model Experience with data modeling approaches such as dimensional modeling or Data Vault Experience with data quality practices Experience with dbt Experience leading a team of around 10 engineers Experience coaching a manager or team lead into an engineering leadership role through hands on collaboration Experience working with distributed teams and external contractors or vendors Experience applying AI in engineering or data work with a concrete example of problem solution tools and outcome English Upper Intermediate or higher Readiness to work on site in Southern California for 4–6 weeks at the start of the engagement Experience with SAP BW/4HANA, SAP Datasphere or migrations from SAP to cloud platforms Snowflake Cortex, Streamlit or semantic layer experience CPG, retail or distribution domain; retailer data platforms or syndicated market data (POS, Nielsen-type datasets) Experience building an engineering operating model or data engineering maturity roadmap Exposure to Microsoft Fabric or Databricks Experience with international client-facing engagements