Data Engineer 324851

Keylent, Inc.

Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Data Science or related field
  • Strong proficiency in Python and SQL
  • Expertise in data analysis
  • Experience building a modern enterprise-wide data and analytics platform
  • Familiarity with data stack technologies like Apache Airflow and DBT
  • AWS experience with data services like Glue and Redshift
  • Excellent communication and collaboration skills

Responsibilities

  • Extract, transform, and load data into the data lakehouse
  • Develop, test, maintain, and document data pipelines using DBT, Spark, AWS Glue and Airflow
  • Build data marts and data cubes for business intelligence
  • Automate data quality checks for accuracy and consistency
  • Collaborate with stakeholders to elicit business requirements
  • Translate business needs into technology solutions
  • Understand the asset management business and financial markets

Benefits

  • Collaborative culture that encourages diverse viewpoints
  • Opportunities for challenging work with significant impact
  • Genuine potential for professional growth and experience
  • Access to smart, talented professionals across business and tech teams
Full Job Description
Data Engineer 324851

***Max rate $80
***Onsite in Baltimore, MD

Data Engineer


Job Summary :

We are seeking a highly skilled and experienced Data Engineer to join our team and play a critical role in building and maintaining our data infrastructure. As a Data Engineer, you will work with smart, talented people across our business and technology teams to ensure that our data is accurate, reliable, and accessible.
Our team is responsible for developing and maintaining data pipelines that will create the core data products in our organization. We ingest data from a variety of internal and external sources; this data is mapped onto our data model to form our foundational data products. You will collaborate with the data governance team to create automatic data quality checks, data reconciliation and monitoring tools. The team is also responsible for creating tailored data products to enable critical business decisions.
We will expect you to be agile and to think outside the box. In return, we will give you challenging work that makes an impact and brings opportunities to gain experience and grow. We help our clients succeed by providing a collaborative culture that encourages every member of our team to bring their point of view to the table.

Responsibilities
• Extract, transform, and load data from various sources into our data lakehouse.
• Develop, test, maintain, and document data pipelines using DBT, Spark, AWS Glue and Airflow.
• Build data marts and data cubes to support various business intelligence initiatives.
• Automate data quality checks to ensure the accuracy and consistency of our data.
Business Knowledge
• Experience collaborating directly with stakeholders, eliciting business requirements, questioning and challenging where necessary.
• Can articulate business needs and translate them into technology solutions.
• An understanding of the asset management business and/or financial markets.
Qualifications
• Bachelor's degree in Computer Science, Data Science or a related field.
• Strong proficiency in Python and SQL.
• Expertise in data analysis.
• Experience building a modern enterprise-wide data and analytics platform.
• Able to quickly learn new technologies and stay abreast of industry trends.
• Experience with data stack technologies, such as Apache Airflow, Prefect, Dagster, Apache Iceberg, DBT, Spark, Great Expectations.
• AWS experience, particularly data services, such as Glue, Lake Formation, EMR, EventBridge, Athena.
• Experience with data warehousing such as Redshift, Snowflake or Dremio.
• Excellent communication and collaboration skills.
Bonus Points
• Experience with DevOps practices such as continuous integration and continuous delivery (CI/CD).
• Experience with data visualization tools such as Tableau or Power BI.
• Experience with metadata management tools (such as Amundsen, Atlas, DataHub, OpenDataDiscovery, Marquez, etc.).

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