Senior Data Engineer

Senior Data Engineer | 68 Years | Hiringhood Phygital Matchday – Hyderabad

Experience:

Job Summary

2 Global Capability Centres (GCCs) and 3 Indian product companies

We are looking for Data Engineers with strong expertise in Python, SQL, PySpark, Apache Spark, ETL/ELT pipelines and cloud data engineering. Candidates should have hands-on experience building scalable, reliable, production-grade data pipelines and modern data platforms.

Key Responsibilities

• Design, develop and maintain scalable data pipelines for data ingestion, transformation and processing.
• Build and optimize ETL/ELT workflows integrating data from multiple sources.
• Develop data processing solutions using Python, SQL and PySpark.
• Work with large datasets using Apache Spark.
• Design and maintain data warehouses, data lakes and lakehouse solutions.
• Implement data quality checks, validation, monitoring and error handling.
• Optimize pipeline performance, scalability and reliability.
• Work with cloud platforms such as AWS, Azure or GCP.
• Collaborate with data scientists, analysts, software engineers and business stakeholders.
• Follow best practices for data security, governance, Git, CI/CD and documentation.

Required Skills

• 6–8 years of relevant Data Engineering experience.
• Strong proficiency 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 PostgreSQL, MySQL, SQL Server or similar databases.
• Familiarity with Apache Airflow or other workflow orchestration tools.
• Understanding of star and snowflake schemas, fact and dimension tables, and slowly changing dimensions (SCDs).
• Knowledge of data quality, pipeline optimization and performance tuning.
• Familiarity with Git and CI/CD practices.

Good-to-Have Skills

• Databricks, Snowflake, Microsoft Fabric, BigQuery or Amazon Redshift.
• Parquet and columnar data formats.
• Kafka or other streaming technologies.
• Delta Lake and lakehouse architecture.
• Docker and data pipeline deployment practices.

Education

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

Hiringhood Phygital Matchday – Selection Process

1. Online Registration:

   Register for the Data Engineer opportunity.

2. Preliminary Online MCQ:

   Complete the initial technical assessment. Qualification is mandatory to attend the in-person Matchday.

3. In-Person Technical Assessment – Hyderabad, 31 October 2026:

   Complete a technical MCQ, executable coding assessment and TARA AI technical interview.

4. Employer Shortlisting:

   Participating employers evaluate candidates based on technical performance, experience and role fit. Additional interview rounds may apply.

Important:

Apply now to participate in Hiringhood Phygital Matchday and explore Data Engineering opportunities across participating organizations.