Data Engineer Manager

3 days ago

Delhi, India Zeno Health Full time
Position Overview We are seeking a highly skilled Lead Data Engineer with expertise in modern data technologies, scalable data infrastructure, and cloud platforms. The ideal candidate will excel in designing and implementing robust data pipelines, managing ETL processes, and leveraging diverse data storage and processing frameworks. This role will focus on optimizing our data infrastructure, ensuring high-quality data delivery, and enabling system observability while collaborating with cross-functional teams to deliver reliable and cost-efficient solutions.
Key Responsibilities
Data Pipeline Development :
Design, build, and maintain scalable data pipelines to support analytics and operational needs, ensuring data quality and integrity.
ETL Processes :
Develop, deploy, and optimize ETL processes using tools like AWS Glue or Apache Airflow.
Data Warehousing :
Manage and optimize large-scale data warehouses (e.g., Amazon Redshift, Google BigQuery), implementing efficient schemas such as Star and Snowflake.
Database Management :
Work with SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB) to handle both structured and unstructured data.
Big Data Frameworks :
Utilize technologies like Apache Spark and Hadoop for large-scale data processing and storage.
Real-Time Monitoring :
Implement solutions for system observability to monitor the health and performance of data pipelines.
Cloud and Cost Optimization :
Leverage AWS services (e.g., Athena, Redshift, DMS) and transition workflows to open-source systems for scalability and cost-effectiveness.
Collaboration and Reporting :
Partner with data scientists, analysts, and business stakeholders to deliver insights using BI tools like Tableau and Retool.
Data Security and Compliance :
Strengthen data security by implementing encryption, access controls, and compliance with governance standards.
Code Maintainability :
Apply object-oriented programming (OOP) principles and SOLID design patterns to ensure clean, maintainable code.
Performance Optimization :
Regularly audit and enhance system performance, ensuring fast data retrieval and high availability.
Required Skills and Qualifications
Technical Expertise :
Proficiency in Python , including libraries like PySpark for large-scale data processing.
Strong knowledge of SQL for analysis and query optimization.
Experience with Big Data technologies like Apache Spark and Hadoop.
Proficient in both relational (SQL) and non-relational (NoSQL) databases.
Data Warehousing and ETL :
Expertise in designing data warehouses using schemas like Star and Snowflake .
Hands-on experience with ETL tools such as AWS Glue or Apache Airflow .
Cloud and DevOps :
Proficient in AWS services like Athena, Redshift, DMS , and other cloud-based data solutions.
Familiarity with DevOps practices and CI/CD pipelines for data workflows.
Data Quality and Monitoring :
Proven ability to implement automated data validation and monitoring systems.
Skills in real-time system observability for pipeline health tracking.
Soft Skills :
Strong analytical and problem-solving skills.
Excellent communication abilities for conveying technical concepts to diverse audiences.
Highly organized, proactive, and able to manage multiple projects efficiently.
Preferred Qualifications
Experience with Apache Kafka or AWS Kinesis for data streaming.
Knowledge of Data Governance and data quality best practices.
Familiarity with performance optimization and cost analysis tools.
Education and Experience
Bachelor’s or Master’s degree in Computer Science, Engineering , or a related field.
Minimum of 5+ years of experience in Data Engineering or a similar role.
Why Join Us?
Work on cutting-edge technologies to build scalable, future-proof solutions.
Collaborate with a talented team to make data-driven decisions.
Enjoy a dynamic work environment that fosters innovation and professional growth.

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