Data Engineer

As a Senior Data Engineer at Mindcurv, you will play a crucial role in designing and implementing scalable data solutions for our clients. You will be part of our dynamic Data and Analytics team, collaborating with cross-functional teams to ensure the organization leverages data as a strategic asset. Your responsibilities will include: - Designing, building, and maintaining scalable data pipelines and ETL processes using Databricks and other modern tools. - Architecting, implementing, and managing cloud-based data warehousing solutions on Databricks (Lakehouse Architecture). - Developing and maintaining optimized data lake architectures to support advanced analytics and machine learning use cases. - Collaborating with stakeholders to gather requirements, design solutions, and ensure high-quality data delivery. - Optimizing data pipelines for performance and cost efficiency. - Implementing and enforcing best practices for data governance, access control, security, and compliance in the cloud. - Monitoring and troubleshooting data pipelines to ensure reliability and accuracy. - Leading and mentoring junior engineers, fostering a culture of continuous learning and innovation. Qualifications required for this role include: - Bachelors or Masters degree in Computer Science or a related field. - 5 years of experience in data engineering roles with a focus on cloud platforms. - Proficiency in Databricks, including Spark-based ETL, Delta Lake, and SQL. - Strong experience with one or more cloud platforms (AWS preferred). - Hands-on Experience with Delta lake, Unity Catalog, and Lakehouse architecture concepts. - Strong programming skills in Python and SQL; experience with Pyspark a plus. - Solid understanding of data modeling concepts and practices (e.g., star schema, dimensional modeling). - Knowledge of CI/CD practices and version control systems (e.g., Git). - Familiarity with data governance and security practices, including GDPR and CCPA compliance. Nice-to-Have Qualifications: - Experience with Airflow or similar workflow orchestration tools. - Exposure to machine learning workflows and MLOps. - Certification in Databricks, AWS. - Familiarity with data visualization tools such as Power BI. In addition to working on cutting-edge projects with innovative technologies, Mindcurv offers a range of perks and benefits, including drinks and snacks, pension scheme, great salary, and a culture of transparency and work-life balance. We value self-starters, team-players, and continuous learners who thrive in an agile and entrepreneurial environment. Join us and embark on an intellectually stimulating journey with constant growth opportunities to enrich your career. If you are ready for the next step in your career and eager to contribute your expertise in data engineering, apply now and be a part of our trailblazing team at Mindcurv. As a Senior Data Engineer at Mindcurv, you will play a crucial role in designing and implementing scalable data solutions for our clients. You will be part of our dynamic Data and Analytics team, collaborating with cross-functional teams to ensure the organization leverages data as a strategic asset. Your responsibilities will include: - Designing, building, and maintaining scalable data pipelines and ETL processes using Databricks and other modern tools. - Architecting, implementing, and managing cloud-based data warehousing solutions on Databricks (Lakehouse Architecture). - Developing and maintaining optimized data lake architectures to support advanced analytics and machine learning use cases. - Collaborating with stakeholders to gather requirements, design solutions, and ensure high-quality data delivery. - Optimizing data pipelines for performance and cost efficiency. - Implementing and enforcing best practices for data governance, access control, security, and compliance in the cloud. - Monitoring and troubleshooting data pipelines to ensure reliability and accuracy. - Leading and mentoring junior engineers, fostering a culture of continuous learning and innovation. Qualifications required for this role include: - Bachelors or Masters degree in Computer Science or a related field. - 5 years of experience in data engineering roles with a focus on cloud platforms. - Proficiency in Databricks, including Spark-based ETL, Delta Lake, and SQL. - Strong experience with one or more cloud platforms (AWS preferred). - Hands-on Experience with Delta lake, Unity Catalog, and Lakehouse architecture concepts. - Strong programming skills in Python and SQL; experience with Pyspark a plus. - Solid understanding of data modeling concepts and practices (e.g., star schema, dimensional modeling). - Knowledge of CI/CD practices and version control systems (e.g., Git). - Familiarity with data governance and security practices, including GDPR and CCPA compliance. Nice-to-Have Qualifications: - Experience with Airflow or similar workflow orchestration tools. - Exposure to machine learning workflow