Our Client, a Financial company, is looking for a Senior Big Data/Machine Learning Engineer for their Richmond, VA/McLean, VA/Plano, TX location.
Responsibilities
- A data engineer on a project team, responsible for designing, building, and optimizing data pipelines and data stores to support various business intelligence and analytical needs.
- This role requires a strong understanding of data warehousing concepts, ETL/ELT processes, and experience working with large-scale distributed systems.
- Design, construct, install, test, and maintain robust data management systems.
- Build high-performance, scalable data pipelines for data ingestion, transformation, and loading using Python, SQL, and cloud services.
- Develop and manage data warehouse solutions (e.g., Redshift, Snowflake) to ensure data integrity and accessibility.
- Collaborate with Data Scientists, Analysts, and other stakeholders to understand data requirements and deliver solutions.
- Implement monitoring and alerting systems for data pipelines to ensure operational stability and data quality.
- Optimize data retrieval and consumption for various analytical use cases.
- Ensure compliance with data governance, security, and privacy policies.
- Evaluate and recommend new technologies and best practices to improve the data infrastructure.
Requirements
- Bachelor’s Degree with at least 6+ years of work experience
- 4+ years of experience in application development including Python, PySpark, SQL, etc.
- 4+ years of experience with a public cloud (AWS preferred)
- 2+ years experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark)
- 4+ years of data warehousing experience (Redshift or Snowflake)
- 2+ years of experience with NoSQL implementation
- 2+ years of experience with databricks.
Why Should You Apply?
- Health Benefits
- Referral Program
- Excellent growth and advancement opportunities
As an equal opportunity employer, ICONMA provides an employment environment that supports and encourages the abilities of all persons without regard to race, color, religion, gender, sexual orientation, gender identity or express, ethnicity, national origin, age, disability status, political affiliation, genetics, marital status, protected veteran status, or any other characteristic protected by federal, state, or local laws.