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# Data Engineer

- **Company:** Robotics Technologies LLC
- **Location:** San Jose, CA, United States
- **Contract:** Temporary contract
- **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Amazon Web Services, Amazon S3, Microsoft Azure, Big Data, Cloud Computing, Cloud Storage, Code Review, Computer Programming, Databases, Continuous Integration, Data Validation, Data Cleansing, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Mart, Data Transformation, Data Security, Data Warehousing, Relational Databases, Database Theory, Software Debugging, Dimensional Modeling, Apache Hadoop, Python (Programming Language), PostgreSQL, Microsoft SQL Server, MySQL, Oracle (Applications), Scrum Methodology, Systems Development Life Cycle, Query Optimization, Power BI, Azure Data Lake, SQL Stored Procedures, SQL Databases, SQL Server Integration Services, Unstructured Data, Data Processing, Freeform SQL, Data Storage Technologies, Cloud Platform System, Azure Data Factory, Informatica Powercenter, Snowflake, Apache Spark, Git, Pyspark, Information Technology, Star Schema, Restful APIs, Azure Synapse Analytics, Software Version Control, Data Pipelines, Jenkins, Databricks
- **Published:** October 31, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=1009c36a4b4e048e

## About the Role

* Programming: Python, SQL, PySpark
 * Big Data: Apache Spark, Hadoop, Databricks
 * ETL Tools: Azure Data Factory, Informatica, SSIS
 * Cloud Platforms: Microsoft Azure, AWS
 * Data Storage: Azure Data Lake, Amazon S3
 * Data Warehousing: Snowflake, Azure Synapse Analytics, SQL Server
 * Databases: PostgreSQL, MySQL, Oracle, SQL Server
 * Data Modeling: Star Schema, Snowflake Schema, Dimensional Modeling
 * DevOps: Git, Azure DevOps, CI/CD, Jenkins
 * Reporting: Power BI
 * Methodologies: Agile, Scrum, SDLC, * Bachelor's degree in Computer Science, Information Technology, or a related field.
 * Experience in data engineering, ETL development, and data pipeline implementation.
 * Strong programming knowledge in Python, SQL, and PySpark.
 * Experience working with cloud platforms and data warehousing technologies.
 * Understanding of data modeling, database concepts, and data integration.
 * Strong analytical, problem-solving, debugging, and communication skills.

## Description

* Designed, developed, and maintained scalable data pipelines to extract, transform, and load data from multiple sources.
 * Developed ETL/ELT workflows using Python, SQL, PySpark, and Azure Data Factory.
 * Built and optimized data processing solutions using Apache Spark and Databricks.
 * Worked with structured and unstructured data from relational databases, APIs, flat files, and cloud storage.
 * Designed and implemented data integration solutions to support business intelligence and analytics requirements.
 * Developed complex SQL queries, stored procedures, views, and functions to transform and process large datasets.
 * Implemented data validation, data cleansing, data transformation, and data quality checks to ensure data accuracy.
 * Worked with Azure Data Lake Storage and cloud-based data platforms to store and manage large volumes of data.
 * Created and maintained data warehouses, data marts, and dimensional data models.
 * Integrated data from multiple enterprise systems using REST APIs and database connectors.
 * Monitored data pipelines, identified failures, and resolved performance and data processing issues.
 * Implemented incremental data loading, partitioning, and optimization techniques to improve pipeline performance.
 * Worked with Snowflake for data loading, transformation, query optimization, and warehouse management.
 * Implemented data security, access controls, and governance practices to protect sensitive business information.
 * Used Git and Azure DevOps for source control, CI/CD, and deployment management.
 * Collaborated with data analysts, data scientists, and business teams to understand data requirements.
 * Participated in Agile/Scrum ceremonies, technical discussions, code reviews, and production support.