Data Engineer

Data Infrastructure & Pipeline Development

1. Design, build, and launch production-ready data models and data pipelines that scale effectively
2. Implement enterprise-grade data governance frameworks and maintain data quality standards
3. Develop and optimize data ingestion processes from various enterprise needs
4. Create efficient data transformation workflows to prepare data for business intelligence ML-AI and Data Products.
5. Partner with data scientists, product managers, and business stakeholders to understand and address data requirements
6. Work closely with business application owners to ensure seamless automation and data management processes
7. Participate actively in Agile ceremonies including daily standups, sprint planning, sprint reviews, and retrospectives
8. Build strong relationships with stakeholders at all levels, from executive to operational teams
9. Lead quality assurance efforts by defining testing strategies and identifying potential risks
10. Ensure timely identification, tracking, and resolution of technical issues

Product & Business Alignment

1. Build deep data expertise and take ownership of data quality for assigned business domains
2. Align development efforts with the product roadmap when building tools and solutions
3. Mature requirements gathering processes and follow Agile methodologies for data product development
4. Proactively adapt to changing business requirements while maintaining solution integrity

What we need to see

Education & Experience

1. Bachelor's degree in Computer Science, Information Systems, or related field (preferably with emphasis on system design and database warehousing/modeling), or equivalent experience
2. 3-5 years of direct experience developing and managing data pipelines for ingestion and transformation
3. Demonstrated expertise with modern cloud data infrastructure and data modeling techniques

Technical Skills

1. Required: Experience with data pipeline development, ETL/ELT processes, and data warehousing concepts, Experience with SQL, Python
2. Preferred: Knowledge of Snowflake, Apache Airflow, and dbt (data build tool)
3. Desired:Cloud infrastructure (AWS, Azure, or GCP)
4. Understanding of data governance principles and best practices

Professional Skills

1. Excellent written and verbal communication skills to effectively convey technical concepts
2. Strong attention to detail and results-oriented mindset
3. Ability to adapt quickly to changing requirements and priorities
4. Commitment to exceptional customer service and quality deliverables
5. Collaborative approach to problem-solving with cross-functional teams
6. Self-motivated with the ability to work independently and as part of a team
7. Effective time management and organizational skills