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Data Engineer

ICONMA, LLC

Painted Post, NY

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JOB DETAILS
SALARY
$34.74–$39.74 Per Hour
SKILLS
Agile Programming Methodologies, Analysis Skills, Apache, Application Programming Interface (API), Automation, Best Practices, Communication Skills, Cross-Functional, Data Analysis, Data Management, Data Migration, Data Modeling, Data Processing, Data Quality, Data Recovery, Data Sets, Database Design, Database Extract Transform and Load (ETL), Database Technology, Detail Oriented, Documentation, Emerging Technology, Health Plan, Identify Issues, Machine Tool, Manufacturing, Operational Audit, Operational Support, Operations Processes, Oracle Database, Painting (Facilities and Maintenance), Performance Tuning/Optimization, PostgreSQL, Problem Solving Skills, Process Improvement, Production Support, Production Systems, Python Programming/Scripting Language, Quality Assurance Methodology, Relational Databases (RDBMS), Root Cause Analysis, SQL (Structured Query Language), Sales Pipeline, Scientific Research, Scripting (Scripting Languages), Software Administration, Software Development, Source Code/Configuration Management (SCM), Sprint Planning, Standup Meetings, System Migration, Team Player, Technical Research, Use Cases, Writing Skills
LOCATION
Painted Post, NY
POSTED
21 days ago
Our Client, a Business Manufacturing and Suppply company, is looking for a Data Engineer for their Painted Post, NY location.
 
Responsibilities:
  • Embed within a cross-functional Agile team, participating in sprint planning, stand-ups, backlog refinement, and technical discussions.
  • Design, build, troubleshoot, and maintain ETL/ELT workflows that support application functionality, analytics, reporting, and scientific workflows.
  • Develop and manage data pipelines using Apache Airflow, ensuring reliable orchestration, scheduling, monitoring, and recovery of data processes.
  • Work with stakeholders including software developers, scientists, and engineers to understand data sources, workflow requirements, and downstream data needs.
  • Extract, transform, validate, and load data across systems, including relational databases such as Postgres SQL and Oracle.
  • Write, optimize, and maintain complex SQL queries, scripts, and transformation logic to support operational and analytical use cases.
  • Troubleshoot data quality issues, ETL failures, pipeline bottlenecks, and schema inconsistencies; identify root causes and implement durable solutions.
  • Support database exploration, data validation, and troubleshooting using tools such as DBeaver and related database utilities.
  • Evaluate and help adopt new data tools and technologies, including lightweight analytics and transformation solutions (e.g. DuckDB) where appropriate.
  • Collaborate with engineering teams to support reliable integration between data pipelines, applications, APIs, and downstream consumers.
  • Assist with schema evolution, data modeling, migration planning, and data consistency across systems.
  • Document pipeline logic, data dependencies, transformation rules, and operational procedures to support maintainability and team knowledge sharing.
  • Help improve data engineering standards, observability, testing practices, and operational reliability across the team.
  • Regularly interact with scientists and engineers to understand research and technical workflows; experience in scientific or research environments is a strong plus.
 
Requirements:
  • Experience designing, building, and troubleshooting ETL/ELT pipelines
  • Hands-on experience with workflow orchestration tools, preferably Apache Airflow
  • Strong experience writing and optimizing SQL
  • Experience working with relational databases, especially Postgres SQL and Oracle
  • Ability to develop and maintain data transformations, validation steps, and pipeline logic across multiple systems
  • Experience with database tools such as DBeaver or similar for query development, exploration, and troubleshooting
  • Familiarity with modern data processing and analytical tools such as DuckDB or interest in evaluating emerging data technologies
  • Understanding of data modeling, schema design, data integrity, and performance tuning
  • Experience troubleshooting pipeline failures, performance issues, and inconsistent or incomplete datasets
  • Familiarity with scripting or programming for pipeline development and automation; Python experience is strongly preferred
  • Understanding of version control and collaborative development workflows
  • Experience supporting production data systems with an emphasis on reliability, maintainability, and clear documentation
  • Confident collaborating with developers, scientists, analysts, and product stakeholders
  • Able to gather and clarify technical and data requirements and translate them into scalable data solutions
  • Strong communication skills around pipeline status, data quality issues, dependencies, and tradeoffs
  • Comfortable handling ambiguity, improving incomplete processes, and helping define best practices
  • Proactive in identifying opportunities to improve data workflows, tooling, performance, and operational stability
  • Strong analytical and problem-solving skills
  • High attention to detail and commitment to data quality, consistency, and reliability
  • Demonstrated initiative in troubleshooting issues and improving pipeline robustness
  • Curiosity and willingness to evaluate and adopt new tools, technologies, and approaches
  • Ability to balance immediate operational needs with long-term maintainability and scalability
  • Comfortable proposing improvements, collaborating across teams, and building trust through reliable execution
 
Why Should You Apply?

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ICONMA, LLC

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