Senior Data Engineer

Senior Databricks Engineer
This position offers you the opportunity to join a fast-growing technology organization that is redefining productivity paradigms in the software engineering industry. Thanks to our flexible, distributed model of global operation and the high caliber of our experts, we have enjoyed triple digit growth over the past five years, creating amazing career opportunities for our people. If you want to accelerate your career working with like-minded subject matter experts, solving interesting problems and building the products of tomorrow, this opportunity is for you.
Position Overview
We are seeking an experienced Sr Databricks Engineer to join our growing data engineering team. This role will be instrumental in designing, developing, and maintaining our enterprise-level data platform using Databricks to support critical banking operations and analytics initiatives.
Key Responsibilities
Design, develop, and optimize data pipelines using Databricks and Apache Spark
Build scalable ETL/ELT processes to ingest, transform, and deliver data from various banking systems
Implement data lakehouse architecture using Delta Lake for reliable data storage and processing
Collaborate with data scientists, analysts, and business stakeholders to understand data requirements
Optimize Databricks cluster configurations and query performance for cost efficiency
Develop and maintain data quality frameworks and monitoring solutions
Implement security best practices and ensure compliance with banking regulations (PCI-DSS, SOX, GDPR)
Create and maintain technical documentation for data workflows and processes
Mentor junior engineers and promote best practices in data engineering
Participate in code reviews and contribute to continuous improvement initiatives
Required Qualifications
Bachelor's degree in Computer Science, Engineering, or related field
5+ years of experience in data engineering or related roles
3+ years of hands-on experience with Databricks platform
Strong proficiency in Apache Spark (PySpark/Scala)
Expert-level SQL skills and experience with large-scale data processing
Experience with Delta Lake and data lakehouse architectures
Solid understanding of cloud platforms (AWS, Azure, or GCP)
Experience with banking or financial services data and regulatory requirements
Knowledge of data modeling, data warehousing concepts, and dimensional modeling
Strong problem-solving skills and attention to detail
Preferred Qualifications
Databricks certification (Data Engineer Associate or Professional)
Experience with real-time streaming data processing (Kafka, Event Hubs)
Knowledge of MLOps and ML model deployment on Databricks
Experience with Infrastructure as Code (Terraform, CloudFormation)
Familiarity with CI/CD pipelines and DevOps practices
Experience with data governance tools and frameworks
Knowledge of Python libraries for data processing (Pandas, NumPy)
Understanding of banking products, risk management, or fraud detection systems
Technical Skills
Databricks Platform & Unity Catalog
Apache Spark (PySpark, Spark SQL, Scala)
Delta Lake & Data Lakehouse Architecture
SQL & NoSQL Databases
Cloud Platforms (AWS/Azure/GCP)
Python & Scala Programming
Git & Version Control
Data Orchestration Tools (Airflow, Azure Data Factory)
Data Visualization Tools (Power BI, Tableau)
What We Offer
Competitive salary and performance-based bonuses
Comprehensive health, dental, and vision insurance
401(k) with company match
Professional development and certification opportunities
Flexible work arrangements
Collaborative and innovative work environment
Opportunity to work on cutting-edge data technologies in the banking sector
About Parser
Parser is a forward-thinking banking company committed to leveraging data and technology to deliver exceptional financial services. We foster a culture of innovation, collaboration, and continuous learning, empowering our teams to drive meaningful impact in the financial industry.

Employment type
Full-Time

Work arrangement
Yes