About the role:
We are looking for a skilled Data Engineer to join our team and help design, build, and maintain reliable data pipelines and scalable data processing solutions. The ideal candidate will have strong experience in Python or similar scripting languages, ETL/ELT development, SQL, and modern data engineering frameworks.
You will work closely with engineering, analytics, and business teams to build efficient data infrastructure that supports reporting, analytics, and data-driven decision-making.
Key Responsibilties:
- Design, develop, and maintain scalable ETL/ELT data pipelines.
- Build data ingestion and transformation workflows from multiple sources.
- Develop efficient and optimized SQL queries for data processing and analytics.
- Work with relational and OLAP databases to support reporting and analytical workloads.
- Develop and maintain data processing workflows using Apache Spark, Apache Airflow, or similar technologies.
- Work with data ingestion tools such as Apache NiFi or equivalent platforms.
- Manage and process data stored in Amazon S3, MinIO, or other object storage systems.
- Implement data transformation, cleansing, validation, and quality checks.
- Design and maintain data models optimized for analytics and reporting.
- Monitor data pipelines and troubleshoot performance, reliability, and data-quality issues.
- Collaborate with backend engineers, analysts, and other stakeholders to understand data requirements.
- Follow best practices for data security, scalability, performance, and maintainability.
- Contribute to improving existing data architecture, processes, and engineering standards.
Required Skills and Qualifications:
- 2–4 years of professional experience in Data Engineering, Backend Engineering, or a related role.
- Strong proficiency in Python, Groovy, or similar scripting languages.
- Good understanding of ETL/ELT pipeline development and data transformation techniques.
- Hands-on experience with SQL and relational databases.
- Experience with OLAP databases such as ClickHouse, Amazon Redshift, or Snowflake is preferred.
- Practical experience with Apache Spark, Apache Airflow, or similar distributed data processing/orchestration frameworks.
- Familiarity with Apache NiFi or equivalent data ingestion tools.
- Experience working with Amazon S3, MinIO, or other object storage systems.
- Good understanding of data modeling principles for analytics and reporting.
- Strong analytical and problem-solving abilities.
- Good communication and collaboration skills.
Preferred Skills:
- Experience working with cloud-based data platforms and services.
- Understanding of distributed systems and large-scale data processing.
- Familiarity with data warehousing and analytics architectures.
- Experience implementing data quality, monitoring, and pipeline observability.
- Knowledge of version control systems such as Git and software development best practices.
What we are looking for:
We’re looking for someone who is analytical, curious, and hands-on, with the ability to work independently while collaborating effectively with cross-functional teams. You should be comfortable working with large datasets, solving complex data problems, and continuously improving data pipelines and infrastructure.
If you enjoy building reliable data systems and turning raw data into structured, actionable information, we’d love to hear from you.
Pay: ₹509,436.64 - ₹800,000.00 per year
Benefits:
- Health insurance
- Leave encashment
- Paid sick time
- Paid time off
- Provident Fund
Work Location: In person
