About the role
About the Role
We are looking for a talented Data Engineer with 2–3 years of experience in building scalable data pipelines and managing large datasets. The ideal candidate should have expertise in SQL, Python, ETL processes, cloud platforms, and data warehousing technologies.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines.
- Build ETL/ELT workflows for data ingestion and transformation.
- Develop and optimize SQL queries for large datasets.
- Work with structured and unstructured data from multiple sources.
- Maintain data quality, integrity, and security.
- Design and manage data warehouses and data lakes.
- Collaborate with Data Analysts, Data Scientists, and Software Engineers.
- Monitor pipeline performance and troubleshoot data issues.
- Create documentation for data architecture and workflows.
Required Skills
- Strong proficiency in SQL and Python.
- Hands-on experience with ETL tools and data integration.
- Experience with Apache Spark, Hadoop, or Kafka.
- Knowledge of cloud platforms such as AWS, Azure, or GCP.
- Experience with data warehousing solutions like Snowflake, Redshift, BigQuery, or Azure Synapse.
- Familiarity with Airflow or similar workflow orchestration tools.
- Understanding of database design and data modeling.
- Experience with Git and version control.
Preferred Skills
- Knowledge of PySpark.
- Experience with real-time data streaming.
- Understanding of data governance and security best practices.
- Familiarity with BI tools such as Power BI or Tableau.
- Strong analytical and problem-solving skills.
Qualification
- Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related field.