Data Engineer III

San Francisco, CA - USA

Monthly Salary: $ 85 - 120

Posted on: 14 hours ago

Vacancies: 1 Vacancy

Job Summary

Application Deadline: Dec. 31 2025
San Francisco
On-site
Hourly salary: $85 - $120

Job Description

Responsibilities :

Responsible for collecting parsing managing analyzing and visualizing large sets of data to turn information into actionable insights.
They will work across multiple platforms to ensure that data pipelines are scalable repeatable and secure capable of serving multiple users.
Design develop and maintain robust and efficient data pipelines to ingest transform catalog and deliver curated trusted and quality data from disparate sources into our Common Data Platform.
Actively participate in Agile rituals and follow Scaled Agile processes as set forth by the CDP Program team.
Deliver high-quality data products and services following Safe Agile Practices.
Proactively identify and resolve issues with data pipelines and analytical data stores.
Deploy monitoring and alerting for data pipelines and data stores implementing auto-remediation where possible to ensure system availability and reliability.
Employ a security-first testing and automation strategy adhering to data engineering best practices.
Collaborate with cross-functional teams including product management data scientists analysts and business stakeholders to understand their data requirements and provide them with the necessary infrastructure and tools.
Keep up with the latest trends and technologies evaluating and recommending new tools frameworks and technologies to improve data engineering processes and efficiencies.

Required Skills:

Bachelors degree in Computer Science Information Systems or a related field or equivalent experience.
2 years experience with tools such as Databricks Collibra and Starburst.
3 years experience with Python and PySpark.
Experience using Jupyter notebooks including coding and unit testing.
Recent accomplishments working with relational and NoSQL data stores methods and approaches (STAR Dimensional Modeling).
2 years of experience with a modern data stack (Object stores like S3 Spark Airflow Lakehouse architectures real-time databases) and cloud data warehouses such as RedShift Snowflake.
Overall data engineering experience across traditional ETL & Big Data either on-prem or Cloud.
Data engineering experience in AWS (any CFS2/EDS) highlighting the services/tools used.
Experience building end-to-end data pipelines to ingest and process unstructured and semi-structured data using Spark architecture.
Requires access to confidential supervisory information

Required Experience:

Application Deadline: Dec. 31 2025 San FranciscoOn-siteHourly salary: $85 - $120Job DescriptionResponsibilities :Responsible for collecting parsing managing analyzing and visualizing large sets of data to turn information into actionable insights.They will work across...

Application Deadline: Dec. 31 2025
San Francisco
On-site
Hourly salary: $85 - $120

Job Description

Responsibilities :

Responsible for collecting parsing managing analyzing and visualizing large sets of data to turn information into actionable insights.
They will work across multiple platforms to ensure that data pipelines are scalable repeatable and secure capable of serving multiple users.
Design develop and maintain robust and efficient data pipelines to ingest transform catalog and deliver curated trusted and quality data from disparate sources into our Common Data Platform.
Actively participate in Agile rituals and follow Scaled Agile processes as set forth by the CDP Program team.
Deliver high-quality data products and services following Safe Agile Practices.
Proactively identify and resolve issues with data pipelines and analytical data stores.
Deploy monitoring and alerting for data pipelines and data stores implementing auto-remediation where possible to ensure system availability and reliability.
Employ a security-first testing and automation strategy adhering to data engineering best practices.
Collaborate with cross-functional teams including product management data scientists analysts and business stakeholders to understand their data requirements and provide them with the necessary infrastructure and tools.
Keep up with the latest trends and technologies evaluating and recommending new tools frameworks and technologies to improve data engineering processes and efficiencies.

Required Skills:

Bachelors degree in Computer Science Information Systems or a related field or equivalent experience.
2 years experience with tools such as Databricks Collibra and Starburst.
3 years experience with Python and PySpark.
Experience using Jupyter notebooks including coding and unit testing.
Recent accomplishments working with relational and NoSQL data stores methods and approaches (STAR Dimensional Modeling).
2 years of experience with a modern data stack (Object stores like S3 Spark Airflow Lakehouse architectures real-time databases) and cloud data warehouses such as RedShift Snowflake.
Overall data engineering experience across traditional ETL & Big Data either on-prem or Cloud.
Data engineering experience in AWS (any CFS2/EDS) highlighting the services/tools used.
Experience building end-to-end data pipelines to ingest and process unstructured and semi-structured data using Spark architecture.
Requires access to confidential supervisory information

Required Experience: