Senior Consultant-Data Engineer

Job Description – Senior Data Engineer / Platform Re-Engineering Lead (Azure Synapse Databricks Migration)

Role Overview We are looking for a highly experienced Senior Data Engineer to lead the re-engineering of an existing enterprise data platform built on Azure Synapse Analytics. The role requires deep technical seniority to audit, understand, and validate a complex end-to-end data architecture spanning source ingestion through to consumption — and to drive a future migration of validated workloads to Databricks. This is not a greenfield role: it demands the ability to reverse-engineer existing implementations, assess their correctness, and own the technical migration strategy.

Key Responsibilities

Lead the technical assessment and re-engineering of an existing enterprise data platform, spanning all layers from source ingestion through to data consumption

Reverse-engineer, document, and validate existing pipeline logic, data models, transformation frameworks, and data governance controls

Identify gaps, defects, and technical debt across the platform and remediate where implementations are incorrect or sub-optimal

Ensure correctness of data processing patterns including change data capture, slowly changing dimensions, deduplication, and business reconciliation

Design and implement target-state architectures aligned to modern lakehouse principles, ensuring feature parity and business logic fidelity during transitions

Manage platform evolution initiatives, including parallel-run phases where multiple implementations operate simultaneously, validating output consistency before cutover

Define and execute migration strategies for existing workloads to modern data platforms, preserving existing governance and control framework semantics

Re-implement ingestion, transformation, and orchestration pipelines on target platforms, maintaining audit, quality, and reconciliation standards

Collaborate with business, data governance, and architecture stakeholders to validate embedded business rules and data quality requirements

Provide technical leadership across re-engineering and migration workstreams, contributing to decommission planning for legacy components

Core Technical Skills

Azure Synapse Data Platform Mandatory hands-on expertise with:

Azure Synapse Analytics (Pipelines, Spark Pool, Dedicated SQL Pool)

Azure Data Lake Storage Gen2 (ADLS Gen2)

Delta Lake on Azure (Synapse Lakehouse patterns)

Oracle Golden Gate Replication for real-time source integration

Azure Analysis Services and Power BI consumption layer patterns

Deep understanding of medallion architecture: Raw / Harmonized / Conformed / Consumption layers

Strong knowledge of SCD Type 0/1/2, CDC patterns, soft/hard delete, and retroactive change processing

Experience with Synapse SQL Pool — stored procedures, control tables, and data quality validation patterns

Experience with audit, balance, and control frameworks — parameterized, modular pipeline governance at enterprise scale

Familiarity with config-driven and automation-first pipeline patterns (YAML, PySpark, SQL-driven generation from mapping documents)

Databricks Lakehouse

Hands-on experience with Azure Databricks (Delta Live Tables, Unity Catalog preferred)

Strong Apache Spark skills (PySpark / Spark SQL)

Experience migrating workloads from legacy data warehouse or Synapse environments to a Databricks Lakehouse

Ability to re-implement governance and control frameworks natively in Databricks (audit logging, reconciliation, DQ checks)

Experience with Delta Lake features: MERGE, CDC, time travel, schema enforcement

Data Engineering Development

Strong Python and SQL programming skills

Experience with ETL/ELT at scale: denormalization, surrogate keys, directory tables, curated data models

Experience integrating complex data sources: Oracle DB, SQL Server, Azure SQL DB, file systems, Salesforce, APIs

Strong data modelling skills: relational, dimensional, and lakehouse-oriented

DevOps Automation

CI/CD pipelines for data engineering (Azure DevOps / GitHub Actions)

Infrastructure as Code (Terraform or ARM)

Containerization (Docker)

Experience with automated testing frameworks for data pipelines (unit testing, reconciliation-based validation)

Nice to Have

Experience with Unity Catalog for data governance and lineage

Familiarity with Azure Purview for data cataloguing and governance

Exposure to real-time and streaming pipelines (Event Hub / Kafka / Kinesis)

Experience with GenAI or ML platform integration (MLOps, feature engineering pipelines)

Familiarity with monitoring and observability tools (e.g., Dynatrace)

Exposure to BI tools (Power BI, Tableau)

Experience Profile

10+ years of experience in Data Engineering, with significant platform migration or re-engineering experience

Proven track record auditing and taking ownership of existing, complex enterprise data platforms — not just building from scratch

Deep knowledge of enterprise data governance patterns: audit trails, reconciliation, data quality controls, SCD versioning

Strong analytical mindset: ability to read existing implementations, identify intent versus defect, and make sound re-engineering decisions

Comfortable operating across both hands-on engineering and technical architecture

Strong communication skills — able to engage business, governance, and engineering stakeholders with clarity

Experience working in regulated or enterprise-scale environments (financial services a plus)

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93014 | Data AI | Professional | Non-Executive | Allianz Services | Full-Time | Permanent

Allianz Group is one of the most trusted insurance and asset management companies in the world. Caring for our employees, their ambitions, dreams and challenges, is what makes us a unique employer. Together we can build an environment where everyone feels empowered and has the confidence to explore, to grow and to shape a better future for our customers and the world around us.

At Allianz, we stand for unity: we believe that a united world is a more prosperous world, and we are dedicated to consistently advocating for equal opportunities for all. And the foundation for this is our inclusive workplace, where people and performance both matter, and nurtures a culture grounded in integrity, fairness, inclusion and trust.

We therefore welcome applications regardless of ethnicity or cultural background, age, gender, nationality, religion, social class, disability or sexual orientation, or any other characteristics protected under applicable local laws and regulations.

Great to have you on board. Let's care for tomorrow.

Note: Having different strengths, experiences, perspectives and approaches is an integral part of Allianz‘ company culture. One means to achieve this is a regular rotation of Allianz Executive employees across functions, Allianz entities and geographies. Therefore, the company expects from its employees a general openness and a high motivation to regularly change positions and collect experiences across Allianz Group.