The company is looking to solve problems related to data processing, analysis, and reporting to drive business decision-making. This involves optimizing data pipelines, automating tasks, ensuring data quality, and providing insights through data models and dashboards.
Requirements
- 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.
Responsibilities
- 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.
- 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.
- Assess schema design and diagnose bottlenecks (e.g., full table scans, inefficient joins).
Other
- 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.
- 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.
- Experience with BI tools such as Tableau, Power BI, or Looker.
- Knowledge of data governance, security, and compliance best practices in a corporate environment.
