Data Engineer- AWS

Role Overview
We are seeking an AWS Data Engineer with 4–7 years of experience to design and build cloud-native data pipelines, contribute to 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, 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.
• Research and experiment with batch and streaming data technologies to evaluate their business impact and suitability for current use cases.
• Contribute to the definition and continuous improvement of data engineering processes and procedures.
• Ensure data integrity, accuracy, and security across corporate data assets.
• Maintain high data quality standards for Data Services, Analytics, and Master Data Management.
• 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 DevOps engineers and architects to improve DataOps tools and frameworks.

Basic Qualifications

• Bachelor’s Degree in Computer Science, Engineering, or related field.
• 4–7 years of experience in application development and data engineering.
• 3+ years of experience with big data technologies.
• 3+ years of experience with cloud platforms (AWS preferred; Azure or GCP also acceptable).
• Proficiency in Python, SQL, Scala, or Java (3+ years).
• Experience with distributed computing tools such as Hadoop, Hive, EMR, Kafka, or Spark (3+ years).
• Hands-on experience with real-time data and streaming applications (3+ years).
• NoSQL database experience (MongoDB, Cassandra) – 3+ years.
• Data warehousing expertise (Redshift or equivalent) – 3+ years.
• UNIX/Linux proficiency including shell scripting – 3+ years.
• Familiarity with Agile engineering practices.
• SQL performance tuning and optimization – 3+ years.
• PySpark experience – 2+ years.
• Exposure to process orchestration tools (Airflow, AWS Step Functions, Luigi, or KubeFlow).

Preferred Qualifications

• Experience with Machine Learning workflows.
• Exposure to Data-as-a-Service platforms.
• Experience designing and deploying APIs.

Excellent communication skills