We are seeking a talented and enthusiastic Data Engineers with 4+ years of experience to join our data engineering team. The ideal candidate will have a strong background in ETL processes, data warehousing, and big data technologies, and will play a key role in building and maintaining our data infrastructure to support analytics and business intelligence needs.

Designation - Lead Data Engineer/Sr. Data Engineer

Work Location - Hyderabad

Experience - 4 - 8 years

Key Responsibilities

• ETL Development:
• Design, develop, and maintain efficient ETL pipelines to process and transform large volumes of data from various sources.
• Implement data transformation and cleansing processes to ensure high-quality data.
• Data Warehouse Development:
• Assist in building and optimizing scalable data warehouse solutions using Snowflake, Data bricks, Redshift, or similar technologies.
• Ensure that data models are efficient, scalable, and support the needs of analytics teams.
• Big Data & Cloud Technologies:
• Utilize AWS Glue and PySpark for processing and transforming large datasets in the cloud.
• Implement data pipelines using Apache Airflow for scheduling and orchestration.
• Database Management:
• Manage and optimize relational databases (RDBMS) to support both transactional and analytical workloads.
• Write efficient SQL queries to support data extraction, reporting, and analytics.
• Collaboration:
• Work closely with your lead and other stakeholders to understand data requirements and deliver reliable data solutions.
• Contribute to the design and architecture of data systems, ensuring alignment with business needs and technical best practices.
• Data Quality & Governance:
• Ensure data integrity, accuracy, and availability through rigorous testing, validation, and monitoring of ETL processes.
• Support data governance initiatives by implementing best practices for data management and security.
  
  

Required Skills & Qualifications

• Education: Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field.
• Experience:
• 4-7 years of experience in data engineering, with a strong focus on ETL processes and data warehousing.
• Hands-on experience with ETL tools and frameworks, as well as Python and PySpark for data processing.
• should have worked with DBT
• Experience with cloud-based data platforms such as AWS Glue, Snowflake, Databricks, or Redshift.
• Proficiency in SQL and experience with RDBMS platforms (e.g., MySQL, PostgreSQL, Oracle).
• Familiarity with data orchestration tools like Apache Airflow.
• Technical Skills:
• Strong understanding of data warehousing concepts and best practices.
• Have hands on DBT (Data Build Tool)
• Experience in building and optimizing data pipelines and workflows.
• Knowledge of cloud infrastructure (AWS, GCP) and data processing technologies.
• Soft Skills:
• Strong analytical and problem-solving skills.
• Excellent communication and teamwork abilities.
• Ability to work in a fast-paced environment and manage multiple tasks simultaneously.
  
  

Preferred Qualifications

• Experience with machine learning pipelines and big data processing.
• Familiarity with DevOps practices and continuous integration/continuous deployment (CI/CD) pipelines.
• Certification in AWS or other relevant cloud platforms.
  
  

Skills: machine learning pipelines,etl processes,aws,redshift,pyspark,snowflake,cloud,data warehousing,data,sql,apache airflow,etl,data bricks,rdbms platforms,big data technologies,cloud infrastructure,devops practices,aws glue,dbt