> Markdown version of [/jobs/ext/4707837-sr-data-engineer](https://www.wearedevelopers.com/jobs/ext/4707837-sr-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). --- # Sr. Data Engineer - **Company:** Judit Inc - **Location:** Plano, TX, United States - **Experience:** Expert - **Contract:** Temporary contract - **Skills:** Airflow, Big Data, BigQuery, Business Process Management, Cloud Database, Capability Maturity Model Integration, Databases, Computer Engineering, Data Architecture, Extract Transform Load (ETL), Data Warehousing, Relational Databases, Apache Hadoop, Hadoop Distributed File System, MapReduce, Apache Hive, Python (Programming Language), Open Source Technology, Cloudera, Shell Script, Software Engineering, SQL Databases, Google Cloud, Apache Spark, Pyspark, Information Technology, Data Management, Stream Analytics - **Published:** November 13, 2026 - **Apply:** https://www.wayup.com/i-j-Sr-Data-Engineer-Judit-Inc-796157777805792/ ## About the Role + Bachelor's degree in a technical field such as computer science, computer engineering, or a related field + 5-7 years of experience designing and implementing large-scale data processing, storage, and distribution systems + Spark on GCP Dataproc (mandatory) + Hands-on experience with large data sets, building big data solutions with the Spark framework, GCP big data services, and industry-standard frameworks + Experience with relational and MPP database platforms such as BigQuery, Hive, and Cloud SQL + Experience with the open-source Hadoop stack and Spark + A strong understanding of big data analytics platforms and ETL for big data + Broad understanding of and experience with real-time analytics + Any combination of the following: o Hadoop: HDFS, MapReduce, Hive, Airflow o Data warehouse: BigQuery, Hive o Languages: Python, PySpark, shell scripting, SQL scripting o Cloud: GCP big data native services o Any RDBMS / DW-BI technologies + Experience working with multi-technology, cross-functional teams and key stakeholders to manage a full life-cycle solution + Hands-on engineering, problem-solving, and communication skills + Process certification, such as Six Sigma, CBPP, BPM, ISO 20000, ITIL, or CMMI ## Description You'll design and build large-scale big data solutions on Google Cloud, with Spark on Dataproc at the center of the work. You'll shape the data architecture, guide the technical implementation from start to finish, and serve as the link between business leadership, technology leadership, and the delivery teams. You'll also lead and mentor other developers on the team. + Design complex, high-performance data architecture + Design, build, test, and maintain highly scalable data management systems and large-scale ETL processes + Provide hands-on help with data modeling and the technical implementation of big data solutions + Lead key engagements and help shape data management processes and IT program plans for the business + Build strong working relationships with senior leaders, learn their business model and pain points, and deliver practical, high-impact results + Guide stakeholders and teams toward the right technology architecture + Find and resolve performance bottlenecks + Lead and mentor other developers + Coordinate with developers, architects, stakeholders, and cross-functional teams + Take part in the full software development life cycle (SDLC) of the big data solution + Produce high-quality work under pressure and on deadline