Senior Data Engineer

🕒 Setembro 18

🏈 Alabama, Nebraska – Remoto

🏈 Alabama – Remote 🌾 Nebraska – Remote

💵 $84.000 - $128.667 / ano

⏰ Tempo Integral

🟠 Sênior

🚰 Engenheiro de Dados

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Protective Life

SiteLinkedInTodas as Vagas

1001 - 5000 funcionários

Fundada em 1908

💸 Finanças

🛡️ Seguros

Finance • Insurance

A Protective Life é uma empresa de serviços financeiros especializada em oferecer seguros de vida e anuidades acessíveis. A empresa oferece uma variedade de produtos de seguro, como apólices de seguro de vida temporário, vida inteira e vida universal, bem como anuidades fixas, imediatas, indexadas e variáveis. A Protective Life auxilia indivíduos no planejamento de seu futuro, incluindo aposentadoria, planejamento patrimonial e proteção financeira para famílias. A empresa enfatiza seu compromisso com a sustentabilidade, envolvimento comunitário e ajuda aos clientes a alcançarem proteção e segurança ao longo de diversas fases da vida. A Protective Life é conhecida por sua forte base financeira e está licenciada para operar em todos os estados, exceto Nova York.

Descrição

• Design, develop, and maintain production data pipelines on Databricks using Python, SQL, Apache Spark, and Delta Lake • Build Bronze-layer ingestion from APIs, relational databases, flat files, cloud storage, and SaaS platforms using dlt and Databricks-native ingestion • Develop Silver-layer transformations in dbt and Python over Delta Lake to cleanse, standardize, deduplicate, validate, conform, and enrich data • Create Gold-layer data products including dimensional models, slowly changing dimensions, fact and bridge tables, aggregates, and serving tables • Produce curated feature and training tables for ML engineering that are versioned and reproducible • Author and maintain data contracts using the Open Data Contract Standard • Implement data quality tests for uniqueness, not-null, referential integrity, accepted values, freshness, and business rules • Orchestrate ingestion and transformation in Dagster Cloud across development, branch, and production deployments • Apply governance through Unity Catalog and manage credentials through Azure Key Vault • Implement incremental and merge-based Delta Lake processing and tune Spark jobs, table layouts, and compute • Troubleshoot production failures, data-quality issues, source-system changes, late-arriving or duplicate data, backfills, and recovery • Participate in the on-call rotation and perform root-cause analysis • Build and maintain CI/CD for data assets in Azure DevOps • Instrument pipelines for freshness, volume, quality, latency, and cost observability with SLA/SLO alerting • Follow least-privilege access, secrets management, change management, and audit controls • Participate in code reviews and document architecture, runbooks, and data products • Collaborate with data architects, analysts, product owners, and business stakeholders to translate requirements into maintainable data solutions

🎯 Requisitos

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field; equivalent practical experience considered • 3+ years building and supporting production data pipelines in a cloud data platform environment • Strong hands-on Python and SQL • Hands-on experience with Databricks or a comparable Spark-based lakehouse, including Delta Lake tables, MERGE, and incremental load patterns • Practical understanding of medallion / multi-layer lakehouse design • Experience ingesting data from APIs, relational databases, files, or SaaS applications, including incremental and state-management problems • Working knowledge of dimensional modeling, ELT design patterns, and data quality practice • Experience with orchestration and scheduling using Dagster, Databricks Workflows, Airflow, Azure Data Factory, or similar • Git-based source control, pull request review, automated testing, and CI/CD; Azure DevOps or comparable • Experience troubleshooting production data failures, performance bottlenecks, and source-system changes • Experience with pipeline monitoring and alerting, including freshness or quality SLAs • Ability to explain technical designs and trade-offs to technical and non-technical partners • Databricks certification or equivalent demonstrated depth preferred • Unity Catalog experience preferred • dbt on Databricks or another Spark transformation framework preferred • Python-based modeling frameworks over Delta Lake, Type 2 history, surrogate keys, and merge strategies preferred • Experience with dlt, Airbyte, Meltano, or Fivetran preferred • Dagster experience with assets, asset checks, sensors, schedules, and branch deployments preferred

🏖️ Benefícios

• Comprehensive health, dental, and vision insurance • Mental health benefits • Employee assistance program • Paid time off • Paid parental leave • Short-term disability • Cultural observance day • Contributions to healthcare accounts • Pension plan • 401(k) plan with Company matching • ProHealth Rewards wellness platform with cash rewards • Annual incentive based on individual and Company performance