01Responsibilities
Provide day-to-day support (50%) for existing data pipelines, jobs, and platforms monitoring, troubleshooting, and resolving issues to ensure smooth operationsDesign, build, and maintain (50%) scalable data pipelines and ETL/ELT workflowsusing Python, SQL, and SparkCollaborate with cross-functional and client teams to understand data requirementsand translate them into technical solutionsPerform rootcause analysis on data/pipeline issues and implement fixes withminimal downtimeOptimize existing data workflows for performance, reliability, and costefficiencyDocument processes, pipeline architecture, and support runbooks for knowledgecontinuityParticipate in oncall/support rotations as needed for the client engagementWork with Databricks and/or AWS cloud environments where applicable to build orsupport data solutionsBasic Qualifications:24 years of experience in a Data Engineering roleStrong proficiency in Python and SQLHandson experience with Apache SparkPrior experience working on client-based projects (mandatory)Ability to work across both support and development responsibilitiesStrong problemsolving and communication skills for clientfacing situationsPreferred Skills:Experience working with DatabricksFamiliarity with AWS Cloud services (e.g., S3, Glue, EMR, Lambda, Redshift)Exposure to CI/CD pipelines for data engineering workflowsExperience with workflow orchestration tools (e.g., Airflow)We are proud to offer a competitive salary alongside a strong insurance package. We pride ourselves on the growth of our employees, offering extensive learning and development resources. .
