Lead / Staff AI Data Engineer - Bangalore

About us

We’re a rare company: according to Handelsblatt (10/24), just 309 public companies worldwide achieved over 20% return on sales for ten consecutive years. Only two are based in Germany and ATOSS is one of them.

With 19 years of record breaking growth, over €2 billion market cap, and listings in SDAX and TecDAX, we’re scaling globally and we’re growing.

The Role

We are building our AI Center of Excellence in Bangalore, bringing together AI, data and engineering expertise to develop the next generation of AI-powered solutions for our products.

A key part of this journey is building the modern data foundation behind our AI initiatives. We are evolving our data landscape towards a scalable lakehouse architecture that can support both traditional data and analytics workloads as well as AI and GenAI use cases.

As a Lead / Staff AI Data Engineer, you will play a key role in shaping this foundation. We are looking for someone who combines strong hands-on data engineering expertise with architectural thinking and has experience modernizing complex data environments.

Key Responsibilities

• Help design and evolve our modern data platform and overall data architecture.
• Play a leading role in migrating existing data warehouse and data lake environments to a modern lakehouse architecture.
• Define architecture, patterns and engineering standards for data ingestion, transformation, storage and serving.
• Build scalable and reliable batch and streaming data pipelines.
• Work hands-on with technologies such as Databricks, Apache Spark, Delta Lake and Kafka.
• Build the data foundations needed for AI and GenAI use cases, including RAG, embeddings and vector-based retrieval.
• Drive data modeling, data quality, governance, lineage, performance and observability.
• Make technical and architectural decisions with a long-term platform perspective.
• Provide technical guidance and mentoring to other data engineers.
• Work closely with AI Engineers, Software Engineers, Product and Architecture teams.

Key Requirements

• Strong hands-on experience in data engineering and data platform architecture, ideally at Lead, Staff or Principal level.
• Proven experience migrating a legacy data warehouse, data lake or comparable data platform to a modern lakehouse architecture.
• Experience defining or significantly contributing to the target architecture and migration strategy, not only implementing individual pipelines.
• Strong experience with Databricks or comparable modern lakehouse technologies.
• Strong knowledge of Apache Spark, Delta Lake or similar technologies.
• Advanced Python and SQL skills.
• Strong experience building production-grade ETL/ELT pipelines across batch and ideally streaming workloads.
• Experience with Azure, AWS or GCP.
• Good understanding of data modeling, data quality, governance, lineage and platform reliability.
• Experience supporting AI/ML or GenAI workloads from a data engineering perspective is a strong advantage.
• Experience with vector databases, embeddings and RAG pipelines is a plus.
• Ability to provide technical direction, challenge existing approaches and influence architectural decisions.
• Strong communication skills and a pragmatic, hands-on approach.

Our Benefits

• Competitive Rewards: Including profit-sharing and employee stock program.
• Structured Onboarding & Continuous Leadership Development: Clear career paths onboarding through Expert & Leadership Tracks, plus access to ATOSS Academy.
• Flexible Work Culture: Hybrid options (remote within the EU), 30 days of vacation, and a strong commitment to diversity & inclusion.
• Engaging Team Environment: Seasonal company events, team retreats, and an in-house barista.
• Health & Wellbeing: Including regular check-ups, corporate wellness programs, and Wellhub membership.
• Stability & Growth: Company listed on SDAX & TecDAX, with 19+ years of record-breaking revenue and a 30%+ EBIT margin. Certified Top Employer© for the 5th year in a row.