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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** SRS Consulting Inc - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Sql Data Warehouse, Application Programming Interfaces (APIs), Agile Methodology, Amazon Web Services, Amazon S3, Batch Processing, Big Data, Cloud Computing, Information Systems, Databases, Continuous Integration, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Warehousing, DevOps, JSON, Python (Programming Language), MongoDB, NoSQL, Cloud Services, Simple Data Format, SQL Databases, Data Streaming, Unstructured Data, Jupyter Notebook, Parquet, Data Processing, Google Cloud, Data Ingestion, Delivery Pipeline, Snowflake, Git, Cloudformation, Pandas, Information Technology, Avro, Functional Programming, Amazon Simple Queue Service (SQS), Terraform, Software Version Control, Data Pipelines - **Published:** July 21, 2026 - **Apply:** https://www.dice.com/job-detail/b72c5704-ed99-4941-a0f7-e5d373d5fde3 ## About the Role USA experience: 4 6 Years Bachelor's or master s degree in Computer Science, Information Systems, or related field * Design data pipelines for API, streaming, and batch processing to facilitate data loads into the Snowflake data warehouse. * Collaborate with other engineering and DevOps team members to implement, test, deploy, and operate data pipelines and ETL solutions. * Develop scripts to Extract, Load and Transform data and other utility functions * Optimize data pipelines, ETL processes, and data integrations for large-scale data analytics use cases * Build necessary components to ensure data quality, monitoring, alerting, integrity, and governance standards are maintained in data processing workflows * Able to navigate ambiguity and thrives in a fast-paced environment. Takes initiative and consistently delivers results with minimal supervision. * 7+ years of experience in building and maintaining data pipelines and ETL/ELT processes in data-centric organizations * Strong coding skills using Python. Familiar with Python libraries related to data engineering and cloud services including pandas, boto, etc. * At least 3 years of experience with AWS S3, SQS, Kinesis, Lambda, AWS DMS, Glue/EMR, AWS Batch or similar services. * Hands-on experience building streaming and batch big data data pipelines * Must have knowledge of building Infrastructure in AWS cloud using Cloud formation or Terraform * Experience on Anakonda and Jupyter Notebook * 3+ years of working experience with Snowflake cloud data warehouse including Snowflake data shares, Snowpipes, Snow SQL, Tasks etc * Must have working knowledge of various databases, SQL and NoSQL * Must have working knowledge of various file formats like CSV, Json Avro, and Parquet. * Hands-on experience with cloud platforms such as AWS and Google Cloud. * Experience working with agile development methodology. * Experienced in CI/CD and release processes, proficient in Git or other source control management systems, to streamline development and deployment workflows Other Desired Skills: * Minimum 5 years of designing and implementing operational production grade large-scale data pipelines, ETL/ELT and data integration solutions. * Exposure to multi-tenant/multi-customer environments is a big plus. * Hands on experience with productionized data ingestion and processing pipelines * Strong understanding of Snowflake Internals and integration of Snowflake with other data processing and reporting technologies. * Experience working with structured, semi-structured, and unstructured data. * Familiarity with MongoDB or similar NoSQL database systems. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [From event streaming to event sourcing 101](https://www.wearedevelopers.com/videos/91-from-event-streaming-to-event-sourcing-101) - [Tips and Tricks for Working with JSON](https://www.wearedevelopers.com/videos/1229-tips-and-tricks-for-working-with-json) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Introducing JSON Structure](https://www.wearedevelopers.com/videos/100219-introducing-json-structure) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers)