Jr Data Engineer (ETL)
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Job Location:
Corning, CA - USA
Monthly Salary:
Not Disclosed
Posted on:
9 hours ago
Vacancies:
1 Vacancy
Job Summary
For further inquiries regarding the following opportunity please contact our Talent Specialist Deepak at
Title: Jr Data Engineer (ETL)
Location: On-site at Corning NY
Duration: 12 Months
Location: On-site at Corning NY
Duration: 12 Months
Work Schedule: Typical 40 hours per week. May require working weekends/holidays or longer days to support projects.
Travel: Limited to no travel required and no on-call requirements.
The manager is open to non-local candidates willing to relocate at their own expenses
Only W2 candidates are eligible for this position. Third-party or C2C candidates will not be considered
Description:
Education and Experience:
This position focuses on Data pipelines & workflows
Bachelors degree in computer science information systems data engineering or related field or equivalent practical experience. May consider an Associate if the candidate has an additional 3-5 years of experience than what is required.
2 years of professional experience in data engineering ETL development or related work or equivalent hands-on experience
Experience or interest in scientific software materials science research environments or technically complex domains is a plus
Scope of Position:
1. Embed within a cross-functional Agile team participating in sprint planning stand-ups backlog refinement and technical discussions.
2. Design build troubleshoot and maintain ETL/ELT workflows that support application functionality analytics reporting and scientific workflows.
3. Develop and manage data pipelines using Apache Airflow ensuring reliable orchestration scheduling monitoring and recovery of data processes.
4. Work with stakeholders including software developers scientists and engineers to understand data sources workflow requirements and downstream data needs.
5. Extract transform validate and load data across systems including relational databases such as Postgres SQL and Oracle.
6. Write optimize and maintain complex SQL queries scripts and transformation logic to support operational and analytical use cases.
7. Troubleshoot data quality issues ETL failures pipeline bottlenecks and schema inconsistencies; identify root causes and implement durable solutions.
8. Support database exploration data validation and troubleshooting using tools such as DBeaver and related database utilities.
9. Evaluate and help adopt new data tools and technologies including lightweight analytics and transformation solutions (e.g. DuckDB) where appropriate.
10. Collaborate with engineering teams to support reliable integration between data pipelines applications APIs and downstream consumers.
11. Assist with schema evolution data modeling migration planning and data consistency across systems.
12. Document pipeline logic data dependencies transformation rules and operational procedures to support maintainability and team knowledge sharing.
13. Help improve data engineering standards observability testing practices and operational reliability across the team.
14. Regularly interact with scientists and engineers to understand research and technical workflows; experience in scientific or research environments is a strong plus.
Technical Skills 2 years (or Commensurate Experience):
1. Experience designing building and troubleshooting ETL/ELT pipelines
2. Hands-on experience with workflow orchestration tools preferably Apache Airflow
3. Strong experience writing and optimizing SQL
4. Experience working with relational databases especially PostgreSQL and Oracle
5. Ability to develop and maintain data transformations validation steps and pipeline logic across multiple systems
6. Experience with database tools such as DBeaver or similar for query development exploration and troubleshooting
7. Familiarity with modern data processing and analytical tools such as DuckDB or interest in evaluating emerging data technologies
8. Understanding of data modeling schema design data integrity and performance tuning
9. Experience troubleshooting pipeline failures performance issues and inconsistent or incomplete datasets
10. Familiarity with scripting or programming for pipeline development and automation; Python experience is strongly preferred
11. Understanding of version control and collaborative development workflows
12. Experience supporting production data systems with an emphasis on reliability maintainability and clear documentation
Team Skills:
1. Confident collaborating with developers scientists analysts and product stakeholders
2. Able to gather and clarify technical and data requirements and translate them into scalable data solutions
3. Strong communication skills around pipeline status data quality issues dependencies and tradeoffs
4. Comfortable handling ambiguity improving incomplete processes and helping define best practices
5. Proactive in identifying opportunities to improve data workflows tooling performance and operational stability
Soft Skills:
1. Strong analytical and problem-solving skills
2. High attention to detail and commitment to data quality consistency and reliability
3. Demonstrated initiative in troubleshooting issues and improving pipeline robustness
4. Curiosity and willingness to evaluate and adopt new tools technologies and approaches
5. Ability to balance immediate operational needs with long-term maintainability and scalability
6. Comfortable proposing improvements collaborating across teams and building trust through reliable execution
Description:
Education and Experience:
This position focuses on Data pipelines & workflows
Bachelors degree in computer science information systems data engineering or related field or equivalent practical experience. May consider an Associate if the candidate has an additional 3-5 years of experience than what is required.
2 years of professional experience in data engineering ETL development or related work or equivalent hands-on experience
Experience or interest in scientific software materials science research environments or technically complex domains is a plus
Scope of Position:
1. Embed within a cross-functional Agile team participating in sprint planning stand-ups backlog refinement and technical discussions.
2. Design build troubleshoot and maintain ETL/ELT workflows that support application functionality analytics reporting and scientific workflows.
3. Develop and manage data pipelines using Apache Airflow ensuring reliable orchestration scheduling monitoring and recovery of data processes.
4. Work with stakeholders including software developers scientists and engineers to understand data sources workflow requirements and downstream data needs.
5. Extract transform validate and load data across systems including relational databases such as Postgres SQL and Oracle.
6. Write optimize and maintain complex SQL queries scripts and transformation logic to support operational and analytical use cases.
7. Troubleshoot data quality issues ETL failures pipeline bottlenecks and schema inconsistencies; identify root causes and implement durable solutions.
8. Support database exploration data validation and troubleshooting using tools such as DBeaver and related database utilities.
9. Evaluate and help adopt new data tools and technologies including lightweight analytics and transformation solutions (e.g. DuckDB) where appropriate.
10. Collaborate with engineering teams to support reliable integration between data pipelines applications APIs and downstream consumers.
11. Assist with schema evolution data modeling migration planning and data consistency across systems.
12. Document pipeline logic data dependencies transformation rules and operational procedures to support maintainability and team knowledge sharing.
13. Help improve data engineering standards observability testing practices and operational reliability across the team.
14. Regularly interact with scientists and engineers to understand research and technical workflows; experience in scientific or research environments is a strong plus.
Technical Skills 2 years (or Commensurate Experience):
1. Experience designing building and troubleshooting ETL/ELT pipelines
2. Hands-on experience with workflow orchestration tools preferably Apache Airflow
3. Strong experience writing and optimizing SQL
4. Experience working with relational databases especially PostgreSQL and Oracle
5. Ability to develop and maintain data transformations validation steps and pipeline logic across multiple systems
6. Experience with database tools such as DBeaver or similar for query development exploration and troubleshooting
7. Familiarity with modern data processing and analytical tools such as DuckDB or interest in evaluating emerging data technologies
8. Understanding of data modeling schema design data integrity and performance tuning
9. Experience troubleshooting pipeline failures performance issues and inconsistent or incomplete datasets
10. Familiarity with scripting or programming for pipeline development and automation; Python experience is strongly preferred
11. Understanding of version control and collaborative development workflows
12. Experience supporting production data systems with an emphasis on reliability maintainability and clear documentation
Team Skills:
1. Confident collaborating with developers scientists analysts and product stakeholders
2. Able to gather and clarify technical and data requirements and translate them into scalable data solutions
3. Strong communication skills around pipeline status data quality issues dependencies and tradeoffs
4. Comfortable handling ambiguity improving incomplete processes and helping define best practices
5. Proactive in identifying opportunities to improve data workflows tooling performance and operational stability
Soft Skills:
1. Strong analytical and problem-solving skills
2. High attention to detail and commitment to data quality consistency and reliability
3. Demonstrated initiative in troubleshooting issues and improving pipeline robustness
4. Curiosity and willingness to evaluate and adopt new tools technologies and approaches
5. Ability to balance immediate operational needs with long-term maintainability and scalability
6. Comfortable proposing improvements collaborating across teams and building trust through reliable execution
Interview Process: Phone screen then either an onsite interview for local candidates or a Teams Meeting for non-local candidates
About us: DivIHN the IT Asset Performance Services organization provides Professional Consulting Custom Projects and Professional Resource Augmentation services to clients in the Mid-West and beyond. The strategic characteristics of the organization are Standardization Specialization and Collaboration. DivIHN is an equal opportunity employer. DivIHN does not and shall not discriminate against any employee or qualified applicant on the basis of race color religion (creed) gender gender expression age national origin (ancestry) disability marital status sexual orientation or military status.
