Data Engineer/Architect - SQL/Python (4-7 yrs)

We are seeking a highly skilled and motivated Data Engineer/Data Architect with 4-7 years of experience to join our team. The ideal candidate will have a strong technical foundation, excellent communication skills, and a solid understanding of data engineering and data warehouse concepts. You will play a key role in designing, building, and optimizing scalable data solutions while maintaining a strong focus on quality and performance.

Key Responsibilities :

- Design, develop, and optimize data pipelines and workflows using tools like SQL, Python, Snowflake, Databricks, and Azure Data Factory (ADF).

- Build and maintain scalable, efficient, and secure data architectures to support business intelligence and analytics needs.

- Develop ETL/ELT processes to extract, transform, and load data from various sources into data warehouses or lakes.

- Ensure data consistency, quality, and reliability across all processes.

- Implement and maintain data warehouse solutions, ensuring adherence to best practices and design principles.

- Collaborate with cross-functional teams to define and implement data models that meet analytical and operational needs.

- Implement robust QA practices to validate data accuracy, consistency, and performance.

- Conduct root cause analysis and resolve data-related issues promptly.

- Work closely with stakeholders, including data analysts, business users, and IT teams, to gather requirements and deliver effective solutions.

- Communicate complex technical concepts in a clear and concise manner to non-technical stakeholders.

Required Skills and Qualifications :

- Strong proficiency in SQL, Python, Snowflake, Databricks, and Azure Data Factory (ADF).

- Solid understanding of data engineering and data warehouse concepts, including dimensional modeling and database optimization.

- Strong analytical and problem-solving skills, with a QA mindset.

- Demonstrated ability to work independently and in a team environment, with a focus on delivering high-quality results.

- Excellent verbal and written communication skills to effectively collaborate with technical and non-technical teams.

- Experience with cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform (GCP).

- Familiarity with data visualization tools like Power BI, Tableau, or similar.

- Knowledge of big data tools like Apache Spark and Kafka.

- Exposure to DevOps practices, including CI/CD pipelines for data engineering workflows.

- Opportunity to work on cutting-edge data engineering projects.

- Be part of a collaborative and innovative team that values creativity and continuous improvement.

- Competitive compensation and growth opportunities.

- Access to state-of-the-art tools and technologies to enhance your skills and career.