Senior Data Engineer - Arlington, VA Hybrid
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Role details
Tech stack
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Job description
As a Senior Data Engineer you will create and enhance scalable data pipelines using established ingestion frameworks, orchestrate workflows with Azure Data Factory, and develop transformations that load trusted data into an Enterprise Data Lake, Delta Lake, and Azure Synapse Analytics dedicated SQL pools. This role also owns testing, technical documentation, data quality configuration, performance optimization, maintenance, and production support for enterprise data solutions.
Your Impact
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Create new batch and streaming data pipelines by leveraging and extending existing data ingestion frameworks and tools.
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Orchestrate, schedule, and monitor data pipelines using Azure Data Factory.
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Develop and enhance data transformations based on business and technical requirements using PySpark, Python, and SQL.
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Parse, transform, and load data into the Enterprise Data Lake, Delta Lake, and Azure Synapse Analytics dedicated SQL pools.
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Build and maintain Databricks data engineering solutions, including Delta Live Tables (DLT), compute configuration, and pipeline maintenance.
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Configure and maintain data quality rules, validation controls, reconciliation processes, monitoring, and automated alerts.
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Perform unit testing and coordinate integration testing and user acceptance testing (UAT) with business and technology partners.
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Create and maintain high-level designs (HLDs), detailed designs (DDs), data mappings, operational runbooks, and support documentation.
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Tune and optimize Databricks, Spark, SQL, and Synapse workloads for performance, reliability, scalability, and cost efficiency.
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Provide production support, including incident troubleshooting, root-cause analysis, defect resolution, and operational maintenance.
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Use Azure DevOps and Git to support source control, CI/CD, release management, and controlled production deployments.
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Collaborate with data architects, analysts, business stakeholders, and support teams to deliver reliable enterprise data products.
Requirements
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Bachelor s degree in Computer Science, Engineering, Information Systems, or a related field.
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4+ years of data engineering experience, including hands-on delivery and support of enterprise data pipelines.
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2+ years of hands-on Azure Databricks data engineering experience.
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Strong experience with Databricks, Delta Live Tables (DLT), Delta Lake, PySpark, Python, SQL, and Spark SQL.
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Strong experience orchestrating data pipelines with Azure Data Factory.
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Experience loading and serving data through Enterprise Data Lake, Delta Lake, and Azure Synapse Analytics dedicated SQL pools.
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Experience configuring Databricks compute, data quality rules, monitoring, maintenance processes, and workload optimization.
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Experience performing unit testing and coordinating integration testing and UAT.
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Experience creating HLDs, detailed designs, data pipeline documentation, and operational runbooks.
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Experience with Azure DevOps, Git, CI/CD pipelines, and production deployment practices.
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Demonstrated experience supporting production data platforms and resolving data pipeline incidents.
Benefits & conditions
As part of our dedication to an inclusive and diverse workforce, Publicis Sapient is committed to Equal Employment Opportunity without regard for race, color, national origin, ethnicity, gender, protected veteran status, disability, sexual orientation, gender identity, or religion. We are also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at hiring@publicis.sapient.com
- An inclusive workplace that promotes diversity and collaboration.
- Access to ongoing learning and development opportunities.
- Competitive compensation and benefits package.
- Flexibility to support work-life balance.
- Comprehensive health benefits for you and your family.
- Generous paid leave and holidays.
- Wellness program and employee assistance.
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