Senior Data Engineer

Senior Data Engineer

Location: Remote

Description :

* Architect and build robust, scalable, and secure data pipelines leveraging Databricks, Apache Spark, and AWS Cloud (EMR, Redshift, S3, Glue, Lambda).

* Participate and represent the data team in critical design discussions with technical leads across various product lines.

* Collaborate closely with application developers, product managers, and business analysts to translate requirements into data models, ETL/ELT workflows, and analytics-ready datasets.

* Conduct pull request reviews and enforce engineering excellence in code quality, testing, and performance optimization.

* Troubleshoot and optimize production data workflows while ensuring observability, resilience, and cost-efficiency at scale.

* Research, evaluate, and apply emerging tools and technologies to continuously modernize the data engineering ecosystem.

* Act as a mentor to junior engineers, fostering a culture of collaboration, innovation, and continuous learning.

Qualifications:

* Bachelor's or master's degree in computer science, Data Engineering, or a related field.

* 7-10 years of professional data engineering experience, including at least 3+ years with modern cloud-based data lake architectures.

* Deep expertise in Apache Spark (PySpark, Scala, or Java) for large-scale distributed data processing.

* Strong experience with Databricks for collaborative data engineering and advanced analytics.

* Hands-on experience with AWS services including EMR, Redshift, S3, Glue, Lambda, IAM, and related cloud-native data tools.

* Proficiency in Python (preferred) as well as Java or Scala.

* Strong understanding of data modeling, data pipelines, and workflow orchestration (Airflow, Step Functions, or similar).

* Solid foundation in algorithms, data structures, and software engineering best practices.

* Excellent communication skills and a proven ability to work cross-functionally with product and engineering teams."