Mindlance
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This range is provided by Mindlance. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range $55.00/hr - $60.00/hr
Direct message the job poster from Mindlance
Responsibilities
Design, build, and maintain scalable data pipelines using AWS Glue and Databricks.
Develop and optimize ETL/ELT processes using PySpark and Python.
Collaborate with data scientists, analysts, and stakeholders to enable efficient data access and transformation.
Implement and maintain data lake and warehouse solutions on AWS (S3, Glue Catalog, Redshift, Athena, etc.).
Ensure data quality, consistency, and reliability across systems.
Optimize performance of large-scale distributed data processing workflows.
Develop automation scripts and frameworks for data ingestion, transformation, and validation.
Follow best practices for data governance, security, and compliance.
Required Skills & Experience
5–8 years of hands‑on experience in Data Engineering.
Strong proficiency in Python and PySpark for data processing and transformation.
Expertise in AWS services — particularly Glue, S3, Lambda, Redshift, and Athena.
Hands‑on experience with Databricks for building and managing data pipelines.
Experience working with large‑scale data systems and optimizing performance.
Solid understanding of data modeling, data lake architecture, and ETL design principles.
Strong problem‑solving skills and ability to work independently in a fast‑paced environment.
Equal Opportunity Employer Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.
Seniority level Mid‑Senior level
Employment type Contract
Job function Information Technology
Industries Banking
#J-18808-Ljbffr
This range is provided by Mindlance. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range $55.00/hr - $60.00/hr
Direct message the job poster from Mindlance
Responsibilities
Design, build, and maintain scalable data pipelines using AWS Glue and Databricks.
Develop and optimize ETL/ELT processes using PySpark and Python.
Collaborate with data scientists, analysts, and stakeholders to enable efficient data access and transformation.
Implement and maintain data lake and warehouse solutions on AWS (S3, Glue Catalog, Redshift, Athena, etc.).
Ensure data quality, consistency, and reliability across systems.
Optimize performance of large-scale distributed data processing workflows.
Develop automation scripts and frameworks for data ingestion, transformation, and validation.
Follow best practices for data governance, security, and compliance.
Required Skills & Experience
5–8 years of hands‑on experience in Data Engineering.
Strong proficiency in Python and PySpark for data processing and transformation.
Expertise in AWS services — particularly Glue, S3, Lambda, Redshift, and Athena.
Hands‑on experience with Databricks for building and managing data pipelines.
Experience working with large‑scale data systems and optimizing performance.
Solid understanding of data modeling, data lake architecture, and ETL design principles.
Strong problem‑solving skills and ability to work independently in a fast‑paced environment.
Equal Opportunity Employer Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.
Seniority level Mid‑Senior level
Employment type Contract
Job function Information Technology
Industries Banking
#J-18808-Ljbffr