Nomiso - Data Quality Analyst - ETL/Python (8-10 yrs)

About Company :

Nomiso is a product and services engineering company. We are a team of Software Engineers, Architects, Managers, and Cloud Experts with expertise in Technology and Delivery Management.

Our mission is to Empower and Enhance the lives of our customers, through efficient solutions for their complex business problems.

At Nomiso we encourage entrepreneurial spirit - to learn, grow and improve. A great workplace, thrives on ideas and opportunities. That is a part of our DNA. We're in pursuit of colleagues who share similar passions, are nimble and thrive when challenged. We offer a positive, stimulating and fun environment - with opportunities to grow, a fast-paced approach to innovation, and a place where your views are valued and encouraged.

We invite you to push your boundaries and join us in fulfilling your career aspirations!

Roles and Responsibilities :

- Review the existing data lake house implementation in Snowflake, identifying opportunities to enhance data quality and integrity.

- Conduct gap analysis of existing data governance and observability tools, proposing improvements for data quality monitoring.

- Define and create reference benchmarks for data quality, ensuring alignment with business needs and industry standards.

- Monitor data pipelines and flows for anomalies, taking proactive steps to resolve data quality issues.

- Collaborate with the Data Governance team to implement data access, governance, and quality standards.

- Develop automated tests and validation checks for data pipelines and quality controls.

- Provide regular status updates on data quality efforts, highlighting key metrics, risks, and actionable next steps.

- Propose and implement actionable steps to improve data quality, reducing errors and improving timeliness in BI solutions delivery.

Must Have Skills :

- 7+ years in data quality management

- Proficiency in SQL for data validation, testing, and analysis.

- Experience with Snowflake or similar cloud data platforms and data lake environments.

- Strong understanding of data quality frameworks, including data validation, error detection, and remediation.

- Experience with data quality tools (e.g., Great Expectations, Talend, Informatica).

- Experience in building automated data validation and quality assurance pipelines.

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- Strong understanding of data governance principles (e.g., data stewardship, data accessibility).

- Problem-solving skills to identify data quality issues and implement effective resolutions.

- Strong communication skills, able to provide clear updates to cross-functional teams and stakeholders.

Good to Have :

- Experience with data observability tools (e.g., Monte Carlo, Datafold, Bigeye).

- Familiarity with Python or other scripting languages for automating data validation and quality tasks.

- Experience with ETL/ELT frameworks (e.g., Apache Airflow, dbt, Talend).

- Familiarity with machine learning models and their impact on data quality.

- Understanding of cloud data architecture and best practices (AWS, Azure, GCP).

- Knowledge of data privacy and compliance regulations (e.g., GDPR, CCPA, HIPAA).

- Experience with Agile methodologies and cross-functional team collaboration.

Qualification :

- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Statistics, or a related field