• Lead the design, development, and optimization of scalable data platforms and pipelines. • Design, build, and maintain production-grade ETL/ELT workflows for batch and near real-time data processing. • Drive the migration and modernization of data assets from BigQuery and other analytical platforms into Snowflake. • Collaborate with business stakeholders, analysts, and engineering teams to translate business requirements into scalable data solutions. • Implement data quality, validation, monitoring, and observability frameworks.

• Reproduce a descriptive-statistics report end-to-end so any figure traces back to raw source — closing the gap the client admitted (numbers they can't currently defend). • Profile and reconcile differing source schemas across acquired entities: map differing field names, types, encodings and business definitions for the same concept into one conformed model. • Build dbt staging → intermediate → mart models with tests; codify the harmonized definitions the Data Science Lead specifies. • Write Great Expectations suites (null / range / uniqueness / referential checks) and wire them into the pipeline so bad data fails loudly rather than silently corrupting analysis. • Implement entity / identity resolution (deterministic + fuzzy matching) where there is no clean shared key for the same customer or account across sources. • Implement and verify anonymization / pseudonymization (hashing / tokenization / k-anonymity) and evidence that re-identification risk is controlled for the client's IT / compliance team. • Optimize Spark / Glue jobs over tens of millions of rows — partitioning, file formats (Parquet), incremental loads, cost control. • Orchestrate with Airflow / Step Functions; build repeatable, scheduled pipelines rather than one-off scripts. • Prepare clean, documented, feature-ready datasets for the PD / delinquency models. • Document runbooks so the offshore team can operate the pipelines and handover takes days, not weeks; help scope onboarding of the remaining (Ireland + additional) sources.

• Define and execute end-to-end SAP data migration strategies. • Develop migration plans, timelines, and cutover activities. • Analyze legacy data structures and business requirements. • Define data mapping rules between source and target systems. • Identify data transformation and enrichment requirements. • Execute migration activities using SAP Migration Cockpit, SAP Data Services, LSMW. • Validate migrated data against business and technical requirements. • Provide hypercare and post-go-live support.

Role Description As a Senior Databricks Consulting Engineer, you will serve as a trusted technical advisor and strategic partner to enterprise customers. You will guide organizations through their data and AI transformation journeys, helping them design, implement, and optimize modern data platforms built on Databricks. You will combine deep technical expertise with strong stakeholder management skills to ensure customers realize measurable value from their Databricks investments. Working alongside client teams, executives, engineers, and Ultra Tendency consultants, you will lead architecture decisions, promote best practices, and drive successful adoption of the Databricks Lakehouse Platform. This is a highly customer-facing role requiring both hands-on technical capability and executive-level communication skills. Key Responsibilities - Customer Advisory & Architecture - Act as the primary technical advisor for strategic Databricks customers. - Design and review scalable data, analytics, and AI architectures leveraging the Databricks Lakehouse Platform. - Lead architecture workshops, solution design sessions, and technical roadmap discussions. - Translate business requirements into technical solutions and implementation plans. - Advise customers on platform modernization, cloud migration, data governance, and AI initiatives. - Solution Delivery & Optimization - Support the successful implementation and adoption of Databricks solutions. - Review data engineering, analytics, machine learning, and GenAI workloads for scalability, performance, security, and cost optimization. - Identify and resolve technical blockers during customer engagements. - Drive architectural best practices for data pipelines, Lakehouse design, Unity Catalog, governance, and platform operations. - Technical Leadership - Serve as a subject matter expert on Databricks capabilities and emerging data & AI technologies. - Mentor customer teams and Ultra Tendency consultants on architecture patterns and best practices. - Deliver executive presentations, technical workshops, and enablement sessions. - Contribute to reusable assets, reference architectures, and practice development initiatives. - Business Development Support - Partner with sales and account teams during strategic customer engagements. - Support technical discovery, solution positioning, and proposal development. - Provide architecture guidance during pre-sales and proof-of-concept activities. - Identify opportunities for platform expansion and increased customer value. Qualifications - 7+ years of experience in data engineering, cloud architecture, analytics, or related fields. - 3+ years working with Databricks in enterprise environments. - Strong expertise in modern data platform architecture and cloud-native solutions. - Hands-on experience designing and implementing Lakehouse architectures. - Strong knowledge of: - Databricks Data Intelligence Platform - Apache Spark - Delta Lake - Unity Catalog - Data Governance & Security - Data Warehousing and Lakehouse Design - ETL/ELT Architectures - Data Modeling - Experience with at least one major cloud platform: - Microsoft Azure (preferred) - AWS - Google Cloud Platform - Proficiency in: - Python - SQL - Spark - Experience engaging with executive stakeholders and technical leadership teams. - Excellent communication and presentation skills in English & German. Preferred Qualifications - Databricks certifications such as: - Databricks Certified Data Engineer Professional - Databricks Certified Solutions Architect - Databricks Certified Machine Learning Professional - Experience with: - Generative AI and LLM solutions - MLflow - MLOps - Data Governance frameworks - Data Mesh architectures - Real-time and streaming data platforms - Experience in consulting or professional services environments. What Success Looks Like - Customers successfully adopt and scale Databricks solutions. - Complex technical challenges are resolved quickly and effectively. - Executive stakeholders view you as a trusted advisor. - Best practices are consistently applied across customer environments. - Customer satisfaction, platform utilization, and business outcomes improve measurably. Benefits - Work with leading enterprise customers across Europe. - Be part of a rapidly growing Data & AI consultancy. - Access to cutting-edge technologies in Data Engineering, Analytics, AI, and GenAI. - Opportunity to shape and expand Ultra Tendency's Databricks practice. - Continuous learning and certification support. - Flexible and remote-friendly working environment. - Competitive compensation package. - Collaborative, entrepreneurial, and international culture. Eligibility - Applicants must currently reside in Germany and possess the legal right to work in the country. - Unfortunately, we are unable to provide relocation assistance or visa sponsorship for this position.