Sr. Data Engineer - GCP/Spark/Scala
Infosys Limited
Raleigh, NC (In Person)
Full-Time
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Job Description
ID 147246BR
Technical Skills 1 Technology|Cloud Platform|GCP Data Analytics Technical Skills 2 Technology|Big Data - Data Processing|Spark Overview The Infosys Retail, Consumer Goods, and Logistics unit stands as a globally respected partner of choice, dedicated to helping clients achieve their business goals through cutting-edge technology and seamless services. Our unit offers a dynamic forum where projects and teams can effectively learn, adopt, and excel in all technologies. We foster a vibrant community that leverages shared skills and experiences to deliver high-quality, value-enhanced solutions. Join us and become part of a team that drives innovation, operational efficiency, and sustainable growth in the retail, consumer goods, and logistics sector. Together, we can shape the future of these industries and achieve remarkable success. In the assigned Job Role of Technology Consultant 2, your Area Of Responsibility will be as below: ⦁ Contribute to the requirements elicitation process by documenting assigned parts of business requirements, in line with guidance provided ⦁ Facilitate software application design discussions, and document design decisions to guide the technical team towards building software solutions ⦁ Participate in coding and integrate new features or updates into existing applications, with a focus on maintaining system stability ⦁ Conduct code reviews, do changes to the codebase and maintain code repositories ⦁ Implement test strategies, analyse results, and coordinate bug fixes to uphold the software quality standards ⦁ Develop user training programs, documentation, and support frameworks to ensure a smooth transition to new software applications ⦁ Actively participate in resolving production issues and recommend preventive strategies to enhance system reliability ⦁ Maintain detailed records of code, testing techniques, and support activities to enrich the knowledge base and assist other similar projects Your contribution to the team: ⦁ A collaborative spirit and excellent communication skills. ⦁ The ability to handle end to end SDLC phases from requirement gathering to implementation. ⦁ A knack for translating complex requirements into actionable development tasks. ⦁ A passion for design and hands-on coding experience ⦁ A proactive approach to testing, troubleshooting, and refining our applications. ⦁ The ability to work with cross-functional teams and do software integration. Required Skill and Experience- Strong hands-on experience with GCP
- Expertise in BigQuery and Google Cloud Storage (GCS)
- Proficiency in Scala and/or Python for data engineering workflows.
- Strong experience with Apache Spark for large scala data processing.
- Experience with Apache Airflow for workflow orchestration.
- Advanced SQL skills for data analysis and transformation.
- Experience implementing CI/CD pipelines. Preferred Skill and Experience
- Strong analytical and problem-solving skills.
- Excellent communication and collaboration abilities.
- Microsoft certifications (e.g., Power BI Data Analyst Associate, Fabric Analytics Engineer) are a plus. Additional Required Qualifications
- Bachelor's degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
- This position may require relocation and/or travel to work/project location.
- Candidates authorized to work for any employer in the United States without employer-based visa sponsorship are welcome to apply.
Additional Details Key Responsibilities:
- Design, develop, and maintain scalable data pipelines on GCP.
- Build and optimize data processing workflows using BigQuery, Spark, and GCS.
- Develop and maintain ETL/ELT pipelines using Scala and Python.
- Orchestrate and schedule data workflows using Apache airflow.
- Write complex and optimized SQL queries for large scale datasets.
- Integrate and process data form multiple sources ensuring data quality and reliability.
- Implement and maintain CI/CD pipelines for automated deployment of data engineering workflows.
- Troubleshoot performance issues and optimize data processing jobs.
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