We are seeking a Data Engineer to support the development, integration, transformation, and quality of enterprise data solutions. The role will work across data pipelines, data modeling, analytics, visualization, and automation to provide reliable, reusable, and business-ready datasets.
The ideal candidate will have strong foundations in SQL and Python, practical knowledge of ETL/ELT and data warehousing, and an interest in modern data architecture, analytics, and AI-enabled automation.
Key Responsibilities
- Develop, maintain, and monitor ETL/ELT pipelines for structured and unstructured data from multiple sources.
- Support data ingestion, transformation, integration, and processing activities.
- Troubleshoot pipeline and data-processing issues to maintain reliable data flows.
Data Quality & Reliability
- Perform data cleansing, validation, reconciliation, and quality checks.
- Identify data inconsistencies and work with relevant teams to resolve data-quality issues.
- Ensure datasets are accurate, consistent, and reliable for downstream analytics and reporting.
Data Modeling & Transformation
- Design and maintain reusable datasets, data models, and semantic layers.
- Apply data warehousing concepts, including dimensional modeling and star schemas.
- Apply appropriate software design patterns and SOLID principles when developing reusable data components.
- Support the development of interactive dashboards and automated reports using Tableau or similar BI tools.
- Prepare analytics-ready datasets to support business KPIs and management reporting.
AI & Automation
- Utilize modern AI-assisted tools to accelerate data querying, scripting, development, and automation.
- Validate AI-generated outputs and ensure compliance with organizational data governance and security standards.
- Identify opportunities to automate repetitive data-engineering activities.
Stakeholder Collaboration
- Work closely with data scientists, software engineers, analysts, and business stakeholders.
- Translate business requirements into structured, scalable, and practical data solutions.
- Communicate technical concepts effectively to both technical and non-technical stakeholders.
Documentation & Governance
- Maintain technical documentation, data dictionaries, data mappings, and operational procedures.
- Follow established data governance, security, and quality standards.
Required Technical Skills
- Strong working knowledge of SQL, including joins, aggregations, subqueries, and data manipulation.
- Proficiency in Python for data processing, scripting, and automation.
- Understanding of ETL/ELT processes and data integration.
- Knowledge of data modeling, dimensional modeling, star schemas, and data warehousing.
- Exposure to Tableau or another BI/data visualization platform.
- Understanding of data quality, validation, and reconciliation techniques.
- Familiarity with software design principles, including SOLID principles and design patterns.
- Exposure to AI-assisted development and automation tools is an advantage.
Soft Skills
- Strong analytical and problem-solving capabilities.
- High attention to detail and data accuracy.
- Good communication and stakeholder-management skills.
- Ability to translate business requirements into technical data solutions.
- Strong willingness to learn and adapt to emerging data technologies.
Preferred Profile
A hands-on, technically curious Data Engineer with a strong foundation in SQL, Python, ETL/ELT, data modeling, and data warehousing who is interested in developing further across modern data platforms, analytics, and AI-driven automation.