Senior Data Engineer(Databricks)

Located near FC College Lahore, this full-time Data Engineering role offers an exciting opportunity to work on-site with a dynamic team. The position requires a professional with over five years of experience who is skilled in designing, building, and maintaining scalable data pipelines and architectures. The working hours are from 3:00 PM to 12:00 AM, providing a unique schedule for focused productivity.

Key Responsibilities

- Design, build, and maintain scalable ETL/ELT pipelines integrating data from internal systems, APIs, and external sources.
- Develop and optimize data architectures, including warehouses and storage solutions, to support efficient data management.
- Cleanse, validate, and transform raw data to prepare it for analytics and reporting purposes.
- Write and optimize complex SQL queries and develop robust data models.
- Manage and monitor data workflows to ensure high performance and reliability.
- Maintain data quality, integrity, consistency, and security across all systems.
- Collaborate closely with analysts and business stakeholders to fulfill reporting and business intelligence needs.
- Automate repetitive data processes to enhance workflow efficiency.
- Document pipelines, datasets, schemas, and infrastructure comprehensively.
- Continuously evaluate and improve the company’s data stack, architecture, and engineering practices.

Required Qualifications

- Minimum of 5 years’ experience in Data Engineering or related fields.
- Strong expertise in SQL and database optimization techniques.
- Proven experience in building and maintaining ETL/ELT pipelines.
- Hands-on experience with Databricks or similar data processing platforms.
- Familiarity with cloud data warehouses such as Snowflake, BigQuery, or Redshift.
- Proficiency in Python for data processing and automation tasks.
- Experience with workflow orchestration tools like Airflow or comparable platforms.
- Solid understanding of data modeling, warehousing concepts, and scalable architecture design.
- Experience working with large datasets and distributed systems.
- Excellent problem-solving and debugging skills.

Preferred Qualifications and Additional Skills

- Experience with Spark, Kafka, or real-time data streaming technologies.
- Exposure to healthcare or SaaS datasets is advantageous.
- Knowledge of data governance and metadata management practices.
- Familiarity with DevOps principles, CI/CD pipelines, or infrastructure automation.
- Experience supporting machine learning pipelines is a plus.

This role is ideal for a data engineering professional looking to contribute to a growing organization by enhancing data infrastructure and enabling data-driven decision-making. The position offers the chance to work with modern data technologies and collaborate with cross-functional teams to drive business insights.