{"id":1588210,"url":"https://alion.io/job/allianz-data-engineer-principal-3003","title":"Data Engineer Principal_3003","company":{"id":1757325,"name":"Allianz","domain":"allianz.com","url":"https://alion.io/company/allianz-com","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Phenom","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Minneapolis, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":110000,"max":150000,"currency":"USD","period":"year","gross":null,"usd_annual":150000},"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"Azure SQL Database","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Docker","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"Amazon Kinesis","optional":true},{"name":"Apache Kafka","optional":true},{"name":"Dynatrace","optional":true},{"name":"Tableau","optional":true}],"status":"closed","first_seen_at":"2026-09-15T02:00:00Z","employer_posted_date":"2026-09-15","last_verified_at":"2026-10-04T20:11:04Z","board_verified":false,"closed_at":"2026-10-04T20:11:04Z","days_open":19,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":19},"description":"We are looking for an experienced Principal Data Engineer to work hands-on on the re-engineering of an existing enterprise data platform built on Azure Synapse Analytics. The role requires strong technical depth to audit, understand, and validate a complex end-to-end data architecture spanning source ingestion through to consumption - and to help deliver the migration of validated workloads to Databricks. This is hands on role and demands the ability to reverse-engineer existing implementations, assess their correctness, and build to an agreed migration strategy.\nKey Responsibilities\nContribute to the technical assessment and re-engineering of an existing enterprise data platform, spanning all layers from source ingestion through to data consumption\nReverse-engineer, document, and validate existing pipeline logic, data models, transformation frameworks, and data governance controls\nIdentify gaps, defects, and technical debt across the platform and remediate where implementations are incorrect or sub-optimal\nEnsure correctness of data processing patterns including change data capture, slowly changing dimensions, deduplication, and business reconciliation\nImplement target-state designs aligned to modern lakehouse principles, ensuring feature parity and business logic fidelity during transitions\nSupport platform evolution initiatives, including parallel-run phases where multiple implementations operate simultaneously, validating output consistency before cutover\nExecute migration of existing workloads to modern data platforms, preserving existing governance and control framework semantics\nRe-implement ingestion, transformation, and orchestration pipelines on target platforms, maintaining audit, quality, and reconciliation standards\nCollaborate with business, data governance, and architecture stakeholders to validate embedded business rules and data quality requirements\nMentor less experienced engineers, review code and designs, and support decommission planning for legacy components\nCore Technical Skills\nAzure Synapse & Data Platform Mandatory hands-on expertise with:\nAzure Synapse Analytics (Pipelines, Spark Pool, Dedicated SQL Pool)\nAzure Data Lake Storage Gen2 (ADLS Gen2)\nDelta Lake on Azure (Synapse Lakehouse patterns)\nOracle Golden Gate Replication for real-time source integration\nAzure Analysis Services and Power BI consumption layer patterns\nDeep understanding of medallion architecture: Raw / Harmonized / Conformed / Consumption layers\nStrong knowledge of SCD Type 0/1/2, CDC patterns, soft/hard delete, and retroactive change processing\nExperience with Synapse SQL Pool - stored procedures, control tables, and data quality validation patterns\nExperience with audit, balance, and control frameworks - parameterized, modular pipeline governance at enterprise scale\nFamiliarity with config-driven and automation-first pipeline patterns (YAML, PySpark, SQL-driven generation from mapping documents)\nDatabricks & Lakehouse\nHands-on experience with Azure Databricks (Delta Live Tables, Unity Catalog preferred)\nStrong Apache Spark skills (PySpark / Spark SQL)\nExperience migrating workloads from legacy data warehouse or Synapse environments to a Databricks Lakehouse\nAbility to re-implement governance and control frameworks natively in Databricks (audit logging, reconciliation, DQ checks)\nExperience with Delta Lake features: MERGE, CDC, time travel, schema enforcement\nData Engineering & Development\nStrong Python and SQL programming skills\nExperience with ETL/ELT at scale: denormalization, surrogate keys, directory tables, curated data models\nExperience integrating complex data sources: Oracle DB, SQL Server, Azure SQL DB, file systems, Salesforce, APIs\nStrong data modelling skills: relational, dimensional, and lakehouse-oriented\nDevOps & Automation\nCI/CD pipelines for data engineering (Azure DevOps / GitHub Actions)\nInfrastructure as Code (Terraform or ARM)\nContainerization (Docker)\nExperience with automated testing frameworks for data pipelines (unit testing, reconciliation-based validation)\nNice to Have\nExperience with Unity Catalog for data governance and lineage\nFamiliarity with Azure Purview for data cataloguing and governance\nExposure to real-time and streaming pipelines (Event Hub / Kafka / Kinesis)\nExperience with GenAI or ML platform integration (MLOps, feature engineering pipelines)\nFamiliarity with monitoring and observability tools (e.g., Dynatrace)\nExposure to BI tools (Power BI, Tableau)\nExperience & Profile\n7+ years of hands-on experience in Data Engineering, including platform migration or re-engineering work\nProven track record working on existing, complex enterprise data platforms - not just building from scratch\nDeep knowledge of enterprise data governance patterns: audit trails, reconciliation, data quality controls, SCD versioning\nStrong analytical mindset: ability to read existing implementations, identify intent versus defect, and make sound re-engineering decisions\nPrimarily hands-on, while comfortable contributing to technical design discussions\nStrong communication skills - able to engage business, governance, and engineering stakeholders with clarity\nExperience working in regulated or enterprise-scale environments (financial services a plus)\nWhat we offer\nWe offer a hybrid work model which recognizes the value of striking a balance between in-person collaboration and remote working\nWe believe in rewarding performance and our compensation and benefits package includes health insurance, company bonus scheme, 401(K) with company match, company paid holidays, paid time off, paid volunteer days, tuition reimbursement, paid parental leave, an employee shares program and employee discounts From career development and digital learning programs to international career mobility, we offer lifelong learning for our employees worldwide and an environment where innovation, delivery and empowerment are fostered.\nThe annualized base pay range for this role is $110,000 - 150,000. The annual base salary range represents a nationwide market range. The actual salary for this position will be determined by a number of factors, including the scope, complexity and location of the role, and the skills, education, training, credentials and experience of the candidate. The base pay is just one component of the ATA total compensation package. As part of our comprehensive compensation and highly rated benefits programs, ATA also offers eligibility for an incentive-based annual bonus.\nAbout Allianz Technology\nAllianz 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.\nWe are united by a shared commitment: to put our customers first and at the centre of everything we do. Their needs inspire our thinking and guide our actions.\nTogether, we can build an environment where everyone feels empowered and confident to explore, grow and shape a better future - for our customers and for 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. The foundation for this is our inclusive workplace, where people and performance both matter, and where integrity, fairness, inclusion and trust are at the heart of our culture.\nWe 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.\nJoin us. Let’s care for tomorrow.\nYou.IT","description_format":"text","description_chars":7689,"description_truncated":false,"requirements":{"experience_years_min":7,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Health insurance","Hybrid work","Parental leave"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-10-01T15:24:41Z"},{"event":"close","at":"2026-10-04T20:11:04Z"}],"visa":[],"liveness":null,"pay":{"stated_usd_annual":150000,"is_top_pay":false},"html_url":"https://alion.io/job/allianz-data-engineer-principal-3003","json_url":"https://alion.io/job/allianz-data-engineer-principal-3003.json","meta":{"generated_at":"2026-10-05T02:25:44Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":3289,"day_limit":5000,"remaining_today":1711,"minute_limit":60,"resets_at":"2026-10-06T00:00:00Z"}}}