Associate Data Engineer-Research Data and Analytics

Associate Data Engineer Graph

Roles & Responsibilities

• Data Engineering & ETL:

  Design, develop, and implement data pipelines,

  ETL/ELT

  processes, and data integration solutions. You'll contribute to data pipeline projects from inception to deployment, managing scope, timelines, and risks.

• Data Modeling & Optimization:

  Contribute to data models and data dictionaries to ensure data accuracy and consistency. You will also be responsible for optimizing large datasets for query performance.

• Collaboration & Innovation:

  Collaborate with global, cross-functional teams, including research scientists, to understand data requirements and design solutions. You will also explore new tools and technologies to improve the

  ETL

  platform's performance.

• Cloud & Security:

  Leverage cloud platforms (

  AWS

  preferred) to build scalable and efficient data solutions. You will also implement data security and privacy measures to protect sensitive data.

• Documentation & Best Practices:

  Adhere to best practices for coding, testing, and designing reusable code. You will also maintain documentation of processes, systems, and solutions in tools like

  Confluence

  .

Qualifications

• A Bachelor's degree with 0-3 years of experience or a Diploma with 4-7 years of experience in Computer Science, IT, or a related field.
• Proficiency in

  SQL

  and

  Python

  for data engineering and scripting tasks.
• Hands-on experience with

  big data

  technologies like

  Databricks

  and

  Apache Spark

  (

  PySpark, SparkSQL

  ).
• A strong understanding of data modeling, data warehousing, and data integration concepts.
• Experience with relational databases (

  Oracle, MySQL, SQL Server, PostgreSQL

  ).
• Knowledge of cloud data platforms (

  AWS

  preferred).
• Experience with data visualization tools (

  Dash, Plotly, Spotfire

  ) is a plus.

• Databricks Certified Data Engineer Professional

  certification is preferred.

Soft Skills

• Problem-Solving:

  Excellent critical-thinking and problem-solving skills, with the ability to work with large, complex datasets.

• Communication:

  Strong communication and collaboration skills, with demonstrated awareness of how to function in a team setting.

• Initiative:

  A high degree of initiative and self-motivation, with a passion for tackling complex challenges in drug discovery.

• Adaptability:

  The ability to learn new tools and technologies to improve platform performance.