> Markdown version of [/jobs/ext/1465930-data-engineer](https://www.wearedevelopers.com/jobs/ext/1465930-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** iSpace Inc - **Location:** New York, NY, United States (Remote available) - **Experience:** Expert - **Contract:** Temporary contract - **Skills:** Agile Methodology, Airflow, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Data Analysis, Big Data, Computer Programming, Computer Engineering, Continuous Integration, Information Engineering, Data Mapping, Data Warehousing, Decision Support Systems, Software Design Patterns, Dimensional Modeling, Distributed Computing Environment, Amazon DynamoDB, Github, Revision Control Systems, Apache Hadoop, Python (Programming Language), Key Management, NoSQL, Operational Databases, Performance Tuning, Unstructured Data, System Availability, Snowflake, Apache Spark, Software Application Programming, Electronic Medical Records, Amazon Relational Database Service, Pyspark, Integration Tests, Information Technology, Low Latency, Apache Flink, No-code Tools, Low-code, Real Time Data, Apache Kafka, Bitbucket, Data Management, Functional Programming, Api Design, Stream Processing, Data Pipelines, Sql Tuning, Serverless Computing, Jenkins, Amazon Redshift - **Published:** July 28, 2026 - **Apply:** https://www.dice.com/job-detail/18d01802-5d6b-4183-a314-2d5df30add27 ## About the Role * Education: Bachelor's degree in Computer Science, Computer Engineering, or relevant field * Work Experience: 7+ years of experience in architecting, designing and building Data Engineering solutions and Data Platforms * Experience in building Data Warehouses/Data Platforms on Redshift/Snowflake * Extensive experience building real-time data processing solutions. * Extensive experience building highly optimized data pipelines and data models for big data processing. * Experience working with data acquisition and transformation tools such as Fivetran and DBT * Experience building highly optimized & efficient data engineering pipelines using Python, PySpark, Snowpark * Experience working with distributed data processing frameworks such as Apache Hadoop, or Apache Spark or Flink * Experience working with real-time data streams processing using Apache Kafka, Kinesis or Flink * Experience working with various AWS Services (S3, EC2, EMR, Lambda, RDS, DynamoDB, Redshift, Glue Catalog) * Expertise in Advanced SQL programming and SQL Performance Tuning * Experience with version control tools such as GitHub or Bitbucket. * Expert level understanding of dimensional modeling techniques * Excellent communication, adaptability, and collaboration skills * Excellent analytical skills, strong attention to detail with emphasis on accuracy, consistency, and quality * Strong logical and problem-solving skills with critical thinking Good to Have: * Experience in designing and building applications using Container and serverless technologies * Experience working with fully automated workflow scheduling and orchestration services such as Apache Airflow * Experience working with semi-structured, unstructured data, No SQL databases * Experience with CI/CD using GitHub Actions or Jenkins * Experience designing and building APIs * Experience working with low-code, no-code platforms ## Description Looking for Senior Data Engineer with a passion for building robust, scalable, efficient, and high-quality Data Engineering solutions to join our Engineering team. If you enjoy designing and building innovative data engineering solutions using the latest tech stack in a fast-paced environment, this role is for you. Primary Job Duties and Responsibilities * Collaborate with and across Agile teams to design and develop data engineering solutions by rapidly delivering value to our customers. * Build distributed, low latency, reliable data pipelines ensuring high availability and timely delivery of data * Design and develop highly optimized data engineering solutions for Big Data workloads to efficiently handle continuous increase in data volume and complexity * Build highly performing real-time data ingestion solutions for streaming workloads. * Adhere to best practices and agreed upon design patterns across all Data Engineering solutions * Ensure the code is elegantly designed, efficiently coded, and effectively tuned for performance * Focus on data quality and consistency, implement processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it. * Create design (Data Flow Diagrams, Technical Design Specs, Source to Target Mapping documents) and test (unit/integration tests) documentation * Perform data analysis required to troubleshoot data related issues and assist in the resolution of data issues. * Focus on end-to-end automation of data engineering pipelines and data validations (audit, balance controls) without any manual intervention * Focus on data security and privacy by implementing proper access controls, key management, and encryption techniques. * Take a proactive approach in learning new technologies, stay on top of tech trends, experimenting with new tools & technologies and educate other team members. * Collaborate with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility, and fostering data-driven decision making across the organization. * Communicate clearly and effectively to technical and non-technical leadership. ## 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) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)