Data Engineer

ProSearch is hiring a Senior Data Engineer in Westbrook, Maine to design and build scalable data pipelines, cloud-based data platforms, data lakes, data warehouses, and distributed data processing solutions that power enterprise analytics and business operations. This hybrid opportunity is ideal for an experienced data engineering professional with expertise in Hadoop, Spark, Python, SQL, data architecture, data integration, and large-scale data management who enjoys solving complex technical challenges and building reliable, high-performance data systems. In this role, you’ll help shape the organization’s data ecosystem by developing robust, fault-tolerant data pipelines, optimizing data storage and processing frameworks, and ensuring trusted access to critical business information. You’ll collaborate with cross-functional teams to support analytics, reporting, application integration, and enterprise data initiatives while helping define best practices for modern data engineering and data governance.

Top Skills

• Data Engineering
• Hadoop, Spark, Hive, Presto & Pig
• Python Development
• SQL (Oracle, PostgreSQL, MySQL)
• Data Pipelines & ETL/ELT
• Data Warehousing & Data Lakes
• NoSQL (Cassandra, MongoDB)
• Cloud Data Engineering
• Distributed Data Processing
• Data Architecture & Integration

What You’ll Do

• Design, build, and maintain scalable data pipelines that collect, process, transform, and deliver large volumes of structured and unstructured data
• Develop and optimize cloud-based and distributed data processing solutions using Hadoop ecosystem technologies
• Build and support data lakes, data warehouses, operational data stores, and enterprise data integration platforms
• Create high-performance SQL queries, database solutions, and data models that support analytics and business intelligence initiatives
• Design reliable backup, recovery, and data management processes to ensure data availability and system performance
• Implement scalable data architecture standards, governance practices, and operational best practices
• Develop automated deployment and integration solutions across distributed environments
• Monitor system performance, troubleshoot data issues, and drive continuous improvements
• Partner with technical and business stakeholders to deliver data solutions that support organizational goals
• Lead efforts to establish standards, processes, and best practices across the data engineering function

• Bachelor’s degree or equivalent combination of education and experience
• Experience building large-scale data pipelines, ETL/ELT workflows, and distributed data processing solutions
• Strong experience with Hadoop technologies, including Spark, Hive, Presto, Pig, and MapReduce
• Advanced SQL experience with Oracle, PostgreSQL, MySQL, or similar platforms
• Python development experience or proficiency in another high-level programming language
• Experience with cloud-based data pipelines and distributed data architectures
• Understanding of NoSQL databases including Cassandra and MongoDB
• Experience with data warehousing, data lakes, and enterprise data management solutions
• Knowledge of software APIs, system integrations, and modern data engineering practices
• Strong problem-solving, communication, customer service, and project management skills

Preferred

• Experience working in Agile or Scrum environments
• Experience supporting enterprise analytics, reporting, and business intelligence initiatives
• Background in designing scalable cloud data platforms and modern data architectures
• Proven ability to balance multiple priorities in fast-paced, evolving environments

• Competitive pay of $63.33-$70.84 per hour depending on experience and expertise
• Opportunity to lead enterprise-scale data engineering initiatives
• Work with big modern data, cloud, and distributed computing technologies
• High visibility role influencing data architecture, data strategy, and engineering best practices
• Collaborative Agile environment focused on innovation and continuous improvement, The salary range for this role reflects the minimum and maximum compensation for the role. Offers are typically made between the range minimum and the range midpoint. Actual compensation will be determined based on job-related skills, experience, and expertise, as evaluated during the interview process. Compensation may also vary based on where a role is performed.