Data Engineer

Data Engineer | Hiringhood Phygital Matchday- Hyderabad 24th and 25th Oct 2026

Job Title: Data Engineer

Experience: 4-8 Years
Employment Type: Full-Time

Job Summary

We are looking for an experienced Data Engineer to design, develop, and maintain scalable data pipelines and data processing solutions. The ideal candidate should have strong expertise in Python, SQL, ETL/ELT pipelines, cloud platforms, and modern data engineering technologies.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines for data ingestion, transformation, and processing.
• Build and optimize ETL/ELT workflows to integrate data from multiple sources.
• Develop data processing solutions using Python, SQL, and PySpark.
• Work with large datasets using distributed processing frameworks such as Apache Spark.
• Design and maintain data warehouses, data lakes, and lakehouse solutions.
• Implement data quality checks, validation, monitoring, and error-handling mechanisms.
• Optimize data pipelines for performance, scalability, and reliability.
• Work with cloud-based data engineering services on AWS, Azure, or Google Cloud Platform.
• Collaborate with data scientists, analysts, software engineers, and business teams.
• Follow best practices for data security, governance, documentation, and version control.

Required Skills

• 48 years of experience in Data Engineering.
• Strong programming skills in Python and SQL.
• Hands-on experience with ETL/ELT pipeline development.
• Experience with Apache Spark and PySpark.
• Knowledge of data warehousing, data lakes, and data modelling.
• Experience with at least one cloud platform: AWS, Azure, or GCP.
• Experience with databases such as PostgreSQL, MySQL, SQL Server, or similar.
• Knowledge of workflow orchestration tools such as Apache Airflow.
• Understanding of data quality, pipeline optimization, and performance tuning.
• Familiarity with Git and CI/CD practices.

Preferred Skills

• Experience with Databricks, Snowflake, Microsoft Fabric, BigQuery, or Amazon Redshift.
• Knowledge of Kafka or other streaming technologies.
• Experience with Delta Lake and lakehouse architecture.
• Familiarity with Docker and data pipeline deployment practices.

Education

Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field.

Keywords

Data Engineer, Python, SQL, PySpark, Apache Spark, ETL, ELT, Data Pipelines, Databricks, Apache Airflow, AWS, Azure, GCP, Snowflake, Data Warehouse, Data Lake, Data Modelling, Big Data.