Data Architect - ETL/Python (9-15 yrs)

Data Integration :

- Design and implement data integration workflows to connect disparate systems (e.g., APIs, ETL/ELT tools, and data lakes).

- Work with stakeholders to understand data requirements and ensure integration aligns with business objectives.

- Maintain and enhance existing integration pipelines for efficiency and reliability.

Data Engineering :

- Develop, test, and deploy scalable and efficient data pipelines using industry-standard tools and programming languages.

- Optimize data storage, retrieval, and processing workflows to meet performance requirements.

- Monitor and troubleshoot data pipelines to ensure consistent data delivery.

Collaboration & Stakeholder Management :

- Partner with data analysts, data scientists, and business teams to provide clean, usable datasets.

- Collaborate with IT and software development teams to ensure smooth deployment of data systems.

Technology & Tools Implementation :

- Evaluate and integrate data management tools (ETL platforms, cloud services, and database systems).

- Ensure compliance with data governance policies, privacy regulations, and security protocols.

Documentation & Reporting :

- Create and maintain comprehensive documentation for data integration and engineering processes.

- Provide regular status updates and reports to stakeholders on data system performance and issues.

Required Skills & Qualifications :

Education :

- Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field.

Technical Skills :

- Proficiency in ETL/ELT tools (e.g., Talend, Informatica, Apache NiFi).

- Strong programming skills in Python, SQL, Scala, or Java.

- Experience with cloud platforms (AWS, Azure, GCP) and services (e.g., S3, Redshift, BigQuery).

- Knowledge of databases (SQL and NoSQL) and data warehouse systems.

- Familiarity with tools like Apache Kafka, Apache Airflow, or similar orchestration platforms.

Soft Skills :

- Strong problem-solving and analytical skills.

- Excellent communication and collaboration abilities.

- Attention to detail with a commitment to quality and accuracy.

Preferred Qualifications :

- Experience in big data technologies (Hadoop, Spark).

- Knowledge of data governance and compliance standards (e.g., GDPR, CCPA).

- Certification in cloud technologies or data engineering tools.