Senior Data Engineer – Databricks

Data Engineer – Databricks Job Overview We are looking for an experienced

Data Engineer

with strong expertise in

Databricks

to design, develop, and optimize scalable data pipelines and modern data platforms. The ideal candidate will have hands-on experience with

big data technologies, cloud platforms, and ETL/ELT processes , with a strong focus on building reliable, high-quality data solutions that support analytics and business intelligence initiatives. The Data Engineer will collaborate closely with

Data Analysts, Data Scientists, Software Engineers, and business stakeholders

to understand requirements and deliver scalable, efficient, and well-governed data solutions. Key Responsibilities Design, develop, and maintain scalable data pipelines using

Databricks . Build and optimize

ETL/ELT workflows

for structured and unstructured data. Develop and manage data ingestion processes from multiple data sources. Process and analyze large-scale datasets using

Apache Spark and PySpark . Design and maintain data models to support analytics and reporting. Optimize data pipeline performance and ensure data accuracy and quality. Collaborate with business and technical stakeholders to understand and translate data requirements. Implement data governance, security, and engineering best practices. Monitor, troubleshoot, and enhance existing data pipelines and data workflows. Document technical designs, processes, and data engineering standards. Contribute to the continuous improvement of data architecture and engineering practices.

Required Qualifications & Skills Bachelor’s degree in

Computer Science, Information Technology, Engineering, or a related field . 5–7 years of experience

in Data Engineering or a similar role. Strong hands-on experience with

Databricks . Strong proficiency in

Apache Spark and PySpark . Strong

SQL

skills and experience working with relational databases. Hands-on experience developing

ETL/ELT data pipelines . Experience with at least one major cloud platform:

Azure, AWS, or GCP . Solid understanding of

data warehousing concepts and dimensional modeling . Experience with version control systems such as

Git . Strong analytical, troubleshooting, and problem-solving skills. Excellent communication and collaboration skills. Preferred Skills Experience with

Delta Lake

and

Lakehouse architecture . Familiarity with

AWS Glue

or equivalent cloud data services. Experience with orchestration tools such as

Apache Airflow . Knowledge of

CI/CD practices

for data engineering. Experience implementing data quality, governance, and monitoring solutions. Databricks or cloud platform certifications

are a plus.

E xperience Requirements 5–7 years

of relevant Data Engineering experience. 2–3+ years of hands-on Databricks experience preferred . Proven experience building and optimizing production-grade data pipelines.