Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Strong employer brand but senior, niche Databricks/AWS requirements limit applicant pool.
Core data engineering skills are transferable, but healthcare BI/governance and Teradata increase domain specificity.
Explicit 8-11 years and mandatory AWS, Databricks, Spark, and BI demands strict filters.
Design and implement scalable cloud-based data solutions using AWS, Databricks, Teradata Vantage, and Microsoft Power Platform to optimize data workflows and support advanced analytics.
Advise teams and stakeholders on data architecture, platform design, engineering best practices, CI/CD processes, and automation strategies to improve efficiency, security, and maintainability.
Provide mentorship, conduct code reviews, and influence technical standards within an agile environment to enable enterprise-wide advanced reporting and analytical capabilities.
8-11 years of experience in application program development or related roles.
Bachelor's degree in Engineering, Computer Science, or related discipline.
Extensive hands-on experience with AWS services including Lambda, Step Functions, CloudTrail, CloudWatch, SNS, SQS, S3, VPC, EC2, RDS, IAM.
Working knowledge of Python, Databricks, SQL, Unix, Microsoft Power Platform technologies, SPARK, and real-time analytics frameworks.
Experienced engineer and advisor comfortable operating in agile, technically rigorous teams with shared ownership and accountability.
Skilled in designing and advising on secure, scalable cloud data architectures and automations to reduce manual interventions and improve data ecosystem performance.
Able to clearly communicate technical designs and solutions to diverse stakeholders and mentor engineers across multiple projects and technologies.