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Senior Data Engineer
Job Location:
Monthly Salary:
Experience Required:
Posted:
13 October 2026 (6 hours ago)
Posted:
Application Deadline:
10 January 2027
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Senior Data Engineer
Summary
We are seeking an experienced Senior Data Engineer to join our IT Services team where you will play a pivotal role in designing building and maintaining robust data infrastructure. This position is critical for ensuring the integrity efficiency and scalability of our data ecosystems enabling advanced analytics and business intelligence initiatives. The ideal candidate will leverage their deep expertise in data architecture and engineering to drive high-quality data solutions that support organizational goals.
Responsibilities
- Design and implement scalable data models and comprehensive data architectures to support enterprise needs.
- Establish and enforce rigorous data validation protocols to ensure high data quality and accuracy across all systems.
- Develop sophisticated error handling mechanisms and logging frameworks to monitor pipeline health and troubleshoot issues efficiently.
- Orchestrate complex data workflows and scheduling using tools such as Apache Airflow Tidal or Control-M.
- Manage version control and automate deployment processes through Git and continuous integration/continuous deployment (CI/CD) pipelines.
- Build and optimize Extract Transform Load (ETL) processes to facilitate seamless data movement and transformation.
- Utilize Databricks PySpark and Spark SQL to process large-scale datasets and perform advanced data engineering tasks.
Requirements
Requirements:
- Possess 5 to 7 years of professional experience in data engineering roles within the IT Services sector.
- Demonstrate strong proficiency in Data Modeling and Data Architecture principles.
- Show proven expertise in Data Validation and Data Quality assurance methodologies.
- Have hands-on experience with Error Handling and Logging strategies in production environments.
- Be skilled in orchestrating workflows using Apache Airflow Tidal or Control-M.
- Display competency in using Git for version control and managing CI/CD pipelines.
- Maintain a solid background in Data Engineering and ETL development.
- Possess practical experience with Databricks PySpark and Spark SQL technologies.
Salary: 6 -8 LPA
Required Skills:
67 years of Data Engineering / ETL experience. Hands-on experience with Databricks PySpark and Spark SQL. Strong SQL including joins aggregations window functions and query optimization. Python scripting and data processing. Cloud data warehouses: Snowflake Redshift or BigQuery. ETL/ELT pipelines and Azure Data Factory or AWS Glue. Data modeling data quality validation and troubleshooting.
Required Education:
Bachelors Degree (MBA Preferred)
