Job summary
Job post source
This job is directly from Papigen
Job overview
The Azure Data Engineer role at Papigen involves building and optimizing ETL pipelines within a Data Lakehouse architecture, impacting the company's data infrastructure and analytics capabilities.
Responsibilities and impact
The candidate will build and maintain ETL processes using ADF, PySpark, and Databricks, convert Informatica ETL workflows to the cloud, ensure data quality and performance, create self-service data products, and collaborate with data architects and business teams.
Experience and skills
The position requires 8+ years of data engineering experience, strong skills in Databricks, PySpark, SQL, Azure, experience with legacy ETL migration, familiarity with financial risk datasets and data marts, and exposure to Agile projects with strong problem-solving skills.
Company overview
Papigen is a technology consulting firm specializing in helping startups and enterprises develop products by focusing on strategy, digital transformation, data, and technology solutions. Based in Washington, DC, with a small team size, Papigen offers services such as software development, data architecture, business analysis, and user experience design, catering to industries like energy, building science, and enterprise software. The company generates revenue through consulting engagements, project management, and technical staffing for roles including data center architects, business analysts, and developers. Papigen’s expertise in big data and digital strategy positions it as a partner for organizations seeking to innovate and optimize their technology infrastructure. Its history reflects a focus on agile, cross-functional teams and a growing presence in both the US and international markets.
How to land this job
Tailor your resume to showcase your 8+ years of data engineering experience, emphasizing expertise in Azure Databricks, ADF, and PySpark, as these are core to Papigen's Data Engineer role.
Highlight your ability to build and optimize ETL pipelines, especially your experience migrating legacy ETL workflows like Informatica to cloud environments, to match the job's key responsibilities.
Apply through multiple channels including Papigen's corporate career site, LinkedIn, and other job boards where the position is posted to maximize your application visibility.
Connect with data engineering and data architecture professionals at Papigen on LinkedIn; use ice breakers like commenting on recent Azure Databricks projects or asking about their approach to building semantic layers for data products.
Optimize your resume for ATS by incorporating keywords from the job description such as 'Azure Databricks,' 'PySpark,' 'ETL pipelines,' 'ADF,' 'semantic layers,' and 'legacy ETL migration' to ensure it passes automated screenings.
Leverage Jennie Johnson's Power Apply feature to automate applying across platforms, tailor your resume for ATS, and identify LinkedIn contacts, allowing you to focus your time on networking and interview preparation.
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