Mindex
software development and cloud services
DataEngineer
“Data Engineer at Mindex. Skills: Data Pipelines, SQL, Python, Cloud Services. Assemble large, complex data sets. Provide operational support and troubleshooting”
What You'll Achieve.
deliver end-to-end solutions; ensure high quality throughput & performance; answer business questions; identify opportunities for improvement
Industry & Context.
solving complex problems; problem-solving skills
What They're Looking For.
Must Have
BS degree in Computer Science, Data Science, Engineering, or equivalent software/services experience, 4+ years working with SQL, Snowflake, Databricks, Spark, 4+ years using Python, SQL, PySpark, R, or similar languages, 4+ years building and optimizing data pipelines, architectures, and data sets, 2+ years supporting large-scale data processing and storage using Azure Data Factory, Integration Runtime, Data Lake, Databricks, Spark, Azure ML, and Cosmos DB, 2+ years addressing privacy, compliance, and security aspects of data storage, 2+ years delivering data solutions in Agile environments, 2+ years with software development and CI/CD methodologies and tools, 2+ years with Ansible Tower, Azure, ARM, Terraform Enterprise, Azure DevOps, and GitHub Actions, 2+ years with Salesforce FSC and Salesforce Data Cloud, Applicants must be authorized to work for ANY employer in the U. S.
Nice to Have
Kubernetes a plus
What You'll Do.
Provide operational support and troubleshooting
Work closely with architects
Deliver automation & efficient processes
Ensure data extraction
transformation and loading meet requirements
Engage with data source platform leads
Create data tools for data scientist team members
How You'll Work.
Team & Collaboration
collaborating with cross-functional teams; work closely with clients, stakeholders, and team members; Work closely with architects, solution leads, data owners, Data Scientists and key stakeholders
Communication Scope
communication skills are important; explain technical concepts to both technical and non-technical audiences
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