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Vanda is seeking a Data Engineer & Analyst to help us process, integrate, and analyze large datasets efficiently. This role is ideal for a hybrid professional with strong experience in data engineering (ETL, automation, and integrations) and data analysis (querying, visualization, and insights generation). The ideal candidate is comfortable working with millions of rows of data, designing automated data pipelines, and optimizing data workflows for business intelligence.

Data Engineer will collaborate with cross-functional teams to ensure our data infrastructure supports business needs efficiently.

Key Responsibilities

Data Engineering & Automation

  • Develop, optimize, and maintain ETL/ELT pipelines to process large datasets from various sources.
  • Automate repetitive data processing tasks, including Excel workbook updates, reporting workflows, and data cleaning.
  • Ensure data quality, accuracy, and security across pipelines, implementing best practices for data integrity and governance.

Data Analysis & Insights

  • Query, analyze, and generate reports from large datasets to drive business decision-making.
  • Develop data models, dashboards, and reports using SQL, Python, or BI tools.
  • Collaborate with cross-functional teams to understand business data needs and provide scalable solutions.

Qualifications

Required Education & Experience:

  • Bachelor’s degree in Computer Science, Information Systems, Data Science, or a related field.
  • Minimum 4 years of experience in data engineering, data analytics, or a related field.

Required Skills:

  • Strong SQL skills, including complex queries, performance tuning, and handling large datasets efficiently.
  • In-depth knowledge of indexing strategies (e.g., B-tree, composite indexes) and when to use them.
  • Experience with partitioning, materialized views, and caching mechanisms for database optimization.
  • Proven ability to assess schema design and diagnose bottlenecks (e.g., full table scans, inefficient joins).
  • Proficiency in scripting with Python, Ruby, or a similar language for automation and data processing.
  • Hands-on experience designing and maintaining ETL/ELT processes and data pipeline automation.
  • Experience with Excel automation using Python, VBA, or Power Query.
  • Strong understanding of data warehousing principles, schema design, and best practices for scalability and performance.

Preferred Skills:

  • Experience with BI tools such as Tableau, Power BI, or Looker.
  • Knowledge of data governance, security, and compliance best practices in a corporate environment.

Soft Skills:

  • Ability to translate complex business needs into efficient technical data solutions.
  • Strong problem-solving skills with the ability to work independently and in a team.
  • Excellent written and verbal communication skills, with the ability to convey technical concepts to non-technical stakeholders.