AWS Engineer

It's fun to work in a company where people truly BELIEVE in what they are doing! We're committed to bringing passion and customer focus to the business. Job Description Role Summary We are looking for a highly motivated Data Engineer with 3–4 years of hands-on experience in AWS Databricks to join our data platform team. The role involves working closely with data scientists, analysts, architects, and business stakeholders to design, build, and maintain scalable, high-performance data pipelines and data solutions within the AWS cloud environment. The ideal candidate should have strong expertise in Databricks, PySpark, SQL, Delta Lake, and AWS data services, along with a good understanding of modern data engineering practices, orchestration, and data governance. Key Responsibilities Design, develop, test, and deploy scalable ETL/ELT pipelines using AWS Databricks, PySpark, and SQL. Build and maintain robust data pipelines for ingesting and processing structured and unstructured data from multiple sources such as Amazon S3, Amazon RDS, APIs, and external platforms. Implement and manage Delta Lake solutions to support both batch and streaming data processing. Optimize Spark workloads for performance, scalability, and cost efficiency. Ensure data quality, consistency, reliability, and integrity through validations, monitoring, exception handling, and reconciliation checks. Collaborate with cross-functional teams including data analysts, data modelers, architects, and business stakeholders to support reporting, analytics, and downstream consumption. Support orchestration and scheduling of pipelines using tools such as AWS Glue Workflows, Apache Airflow, or AWS Step Functions. Participate in CI/CD implementation and code deployment processes using Git, AWS CodePipeline, and CodeBuild. Apply best practices related to data governance, metadata management, security, and access control. Support production issue resolution, ad hoc data requests, and continuous improvement of the data platform. Required Skills and Qualifications Bachelor's degree in Computer Science, Information Systems, Engineering, or a related discipline. 3–4 years of experience in Data Engineering or a similar role. Strong hands-on experience with AWS Databricks. Good proficiency in PySpark and SQL for large-scale data processing. Experience working with Delta Lake and modern lakehouse concepts. Familiarity with AWS services such as Amazon S3, Amazon RDS, AWS Glue, AWS Lambda, and Amazon Redshift. Knowledge of batch and streaming data architectures. Experience with workflow orchestration, monitoring, and debugging of pipelines. Understanding of version control and CI/CD practices. Awareness of data security, governance, and metadata management principles. Strong analytical, problem-solving, and communication skills. Preferred Qualifications Experience in building data pipelines in enterprise-scale cloud data platforms.