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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. * Familiarity with real-time / streaming frameworks and event-driven architectures. * Exposure to data quality frameworks, reconciliation processes, and operational monitoring. * Working knowledge of infrastructure automation and cloud deployment best practices. * Experience collaborating in agile delivery environments.
KEY COMPETENCIES
* Strong problem-solving orientation * Attention to detail and focus on data quality * Ability to work in a fast-paced, collaborative environment * Good stakeholder communication and coordination skills * Ownership mindset with a focus on delivery excellence
NICE TO HAVE
* Experience with data modeling and analytics enablement * Exposure to DevOps and platform engineering practices * Certification in AWS or Databricks technologies
WHY JOIN US
This role offers the opportunity to work at the forefront of cloud-based data engineering, partnering with talented data scientists, analysts, and architects to build scalable, high-impact data solutions on AWS Databricks.
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
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