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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.
Job Responsibility:
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
Requirements:
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)