Aws data engineer

21 hours ago

Bhavnagar, India Infarsight Full time

About Infarsight At Infarsight, we simplify complex operations across Finance, HR, Operations, and Supply Chain through intelligent platforms like Task Sight, Trip Sight, and Fleet Sight. Our engineering teams build scalable software, and our data solutions unlock real-time insights that help businesses move faster and smarter. Role Overview We are seeking a seasoned AWS Data Engineer to design and build cloud-native data pipelines, drive innovation in data engineering practices, and collaborate across teams to deliver secure, scalable, and high-quality data solutions. This role is critical to enabling real-time insights and supporting our mission to streamline enterprise operations. Key Responsibilities Develop, test, deploy, orchestrate, monitor, document, and troubleshoot cloud-based data pipelines and automation workflows in alignment with best practices and security standards. Collaborate with data scientists, architects, ETL developers, and business stakeholders to capture, format, and integrate data from internal systems, external sources, and data warehouses. Lead research and experimentation with batch and streaming data technologies to evaluate their business impact and suitability for current use cases. Advocate for and enable the adoption of emerging data engineering technologies across teams. Contribute to the definition and continuous improvement of data engineering processes and procedures. Mentor ETL developers transitioning into cloud-based data engineering roles. Ensure data integrity, accuracy, and security across all corporate data assets. Maintain high data quality standards for Data Services, Analytics, and Master Data Management. Own the design, development, testing, and delivery of technical solutions. Build automated, scalable, and test-driven data pipelines. Apply software development practices including Git-based version control, CI/CD, and release management to enhance AWS CI/CD pipelines. Partner with Dev Ops engineers and architects to improve Data Ops tools and frameworks. Basic Qualifications Bachelor’s Degree in Computer Science, Engineering, or related field. 10+ years of experience in application development (excluding internships). 4+ years of experience in big data technologies. 4+ years of experience with cloud platforms (AWS, Azure, or GCP). Proficiency in Python, SQL, Scala, or Java (4+ years). Experience with distributed computing tools such as Map Reduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or My SQL (4+ years). Hands-on experience with real-time data and streaming applications (4+ years). No SQL database experience (Mongo DB, Cassandra) – 4+ years. Data warehousing expertise (Redshift) – 4+ years. UNIX/Linux proficiency including shell scripting – 6+ years. Agile engineering practices – 8+ years. SQL performance tuning and optimization – 8+ years. Py Spark experience – 4+ years. Process orchestration tools (Airflow, Kube Flow, AWS Step Functions, Luigi) – 3+ years. Preferred Qualifications 3+ years of experience with Machine Learning workflows. Experience building Data-as-a-Service platforms. Experience designing and deploying APIs.

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