Data Engineer

Armstrong Fluid Technology

$80K — $110K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Information Technology, Data Science or related field
  • 3-5 years of experience in data engineering or analysis
  • Proficiency in SQL and experience with SQL servers
  • Strong knowledge of Python and its data libraries (e.g., Pandas, NumPy)
  • Experience with AWS services (S3, Redshift, Glue, EKS)
  • Extensive experience with PowerBI
  • Familiarity with containers and Kubernetes, C# and .NET is a plus.

Responsibilities

  • Extract, transform, and load (ETL) data from multiple sources
  • Clean and preprocess data for accuracy and reliability
  • Design, develop, and maintain data warehouses
  • Optimize data warehouse performance and ensure integrity and security
  • Design and create comprehensive PowerBI reports and dashboards
  • Implement advanced PowerBI features for report functionality
  • Collaborate with cross-functional teams to understand data requirements
  • Leverage AWS services for data storage, processing, and management.

Benefits

  • Opportunities for professional development and training
  • Collaborative work environment
  • Access to cutting-edge technology
  • Flexible work arrangements
  • Potential for career advancement
Full Job Description
This role involves hands-on work with data from various sources, including SQL servers, APIs, and more. The ideal candidate will be responsible for cleaning and transforming data, creating rich PowerBI reports, developing data warehouses, and performing ETL operations. Familiarity with Python and AWS services related to data management is essential, while knowledge of C# and .NET is a plus.

Key Responsibilities:
  • Extract, transform, and load (ETL) data from multiple sources such as SQL servers, APIs, and other data repositories.
  • Clean and preprocess data to ensure accuracy and reliability.
  • Design, develop, and maintain data warehouses to support business intelligence and analytics.
  • Optimize data warehouse performance and ensure data integrity and security.
  • Design and create comprehensive PowerBI reports and dashboards to visualize data insights and support decision-making processes.
  • Implement advanced PowerBI features such as DAX calculations, custom visuals, and data modeling to enhance report functionality.
  • Collaborate with cross-functional teams to understand data requirements and deliver solutions.
  • Utilize Python for data manipulation and automation tasks.
  • Leverage AWS services for data storage, processing, and management.
  • Implement best practices for data governance and security.
  • Perform data analytics to identify trends, patterns, and insights that drive business strategies and improvements.
  • Utilize containers and Kubernetes for deploying and managing data solutions.


Required Background:
  • Bachelor's degree in computer science, Information Technology, Data Science, or a related field.
  • Minimum of 3-5 years of experience in data engineering, data analysis, or a similar role.
  • Proficiency in SQL and experience with SQL servers.
  • Strong knowledge of Python and its data-related libraries (e.g., Pandas, NumPy).
  • Experience with AWS services such as S3, Redshift, Glue, and EKS.
  • Extensive experience with PowerBI for report creation, visualization, and data modeling.
  • Proven experience in designing, developing, and maintaining data warehouses.
  • Understanding of ETL processes and data warehousing concepts.
  • Familiarity with containers and Kubernetes.
  • Knowledge of C# and .NET is a plus.


Skills and Competencies:
  • Excellent problem-solving and analytical skills.
  • Strong communication and collaboration abilities.
  • Ability to work independently and as part of a team.
  • Detail-oriented with a focus on data accuracy and quality.
  • Adaptable and able to manage multiple tasks simultaneously.
  • Proficiency in data analytics techniques and tools to derive actionable insights from complex datasets.


If you are passionate about data and eager to make an impact, we would love to hear from you!

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