Data Engineer and Insights Analyst
New
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Adept Consulting ServicesData engineering and analytics
Workable workplace: remote; Workable locations: Harrisburg, Pennsylvania, United StatesFull-Time
Salary not disclosed
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Job Details
- Required Skills
- AWSSQLApache Airflow
Requirements
- Be proficient in SQL, including writing complex queries and working with relational databases.
- Have experience building and maintaining data pipelines and integrating data from multiple sources.
- Have experience developing dashboards, reports, or analytical tools that answer business questions.
- Have experience validating data quality and investigating data or workflow issues.
- Be able to explain analytical findings and technical concepts to different audiences.
- Be able to organize work, communicate priorities, and collaborate across teams.
- Be able to handle sensitive information appropriately.
- Preferred: experience with AWS services such as S3, Glue, Redshift, EMR, Athena, Kinesis, or Lambda.
- Preferred: experience with Apache Airflow, AWS Step Functions, or similar orchestration tools.
- Preferred: experience with large datasets, unstructured data, stream processing, or message queuing.
- Preferred: experience supporting statistical analysis, predictive modeling, or machine learning.
- Preferred: experience with data governance, metadata management, or system migrations.
Responsibilities
- Design, build, and maintain scalable data pipelines and analytical data environments.
- Integrate, clean, and transform data from multiple systems to meet documented requirements.
- Develop and maintain cloud-based data solutions and orchestration workflows.
- Implement data validation, monitoring, logging, and alerts to support reliable data delivery.
- Create dashboards, reports, and analytical models for technical and non-technical audiences.
- Investigate data issues, identify root causes, and recommend improvements.
- Automate manual processes and improve workflow performance, reliability, and scalability.
- Collaborate with analysts, data scientists, business leaders, and other stakeholders to develop data products.
- Support data conversions and migrations associated with system upgrades or replacements.
- Maintain documentation for data sources, definitions, structures, workflows, and dependencies.
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