What are the responsibilities and job description for the Lead Data engineer - c2c - candidate must be local to San Francisco, CA (posted by Sid) position at Global Force USA?
Job Details
Role: Lead Data Engineer c2c
Duration: Long Term contract
Location: San Francisco, CA
Required Skills
- Python and PySpark. Kafka and Kafka streams. MySQL and MySQL Heat. Azure Delta Lake. ETL processes. Kafka integrations using Spring Boot Java. Data streaming with Spark.
Additional Skills
- Experience with Delta Lake on Azure Tableau or similar data visualization tools Unity Catalog in Databricks Airflow for pipeline management
Responsibilities
Development Tasks:
- Collect metrics based on user interactions.
- Visualize data for business teams.
- Develop and redesign data pipelines using Kafka streams.
- Implement solutions using Spring Boot Java and Databricks Spark streaming.
Leadership Duties:
- Lead the measurement processes from requirements gathering to production delivery.
- Collaborate with other team leads, business partners, and product managers.
- Balance between hands-on engineering (50%) and team leadership (50%).
Collaboration Structure:
- Onsite: Lead role (this resource)
o Nearshore: Senior developer.
o Offshore: Data engineer role.
Lead Data Engineer - Job Description
Required Skills & Experience:
- Hands-on code mindset with deep understanding in technologies / skillset and an ability to understand larger picture.
- Sound knowledge to understand Architectural Patterns, best practices and Non-Functional Requirements
- Overall, 8-10 years of experience in heavy volume data processing, data platform, data lake, big data, data warehouse, or equivalent.
- 5 years of experience with strong proficiency in Python and Spark (must-have).
- 3 years of hands-on experience in ETL workflows using Spark and Python.
- 4 years of experience with large-scale data loads, feature extraction, and data processing pipelines in different modes near real time, batch, realtime.
- Solid understanding of data quality, data accuracy concepts and practices.
- 3 years of solid experience in building and deploying ML models in a production setup. Ability to quickly adapt and take care of data preprocessing, feature engineering, model engineering as needed.
- Preferred: Experience working with Python deep learning libraries like any or more than one of these - PyTorch, Tensorflow, Keras or equivalent.
- Preferred: Prior experience working with LLMs, transformers. Must be able to work through all phases of the model development as needed.
- Experience integrating with various data stores, including:
o SQL/NoSQL databases
o In-memory stores like Redis
o Data lakes (e.g., Delta Lake)
- Experience with Kafka streams, producers & consumers.
- Required: Experience with Databricks or similar data lake / data platform.
- Required: Java and Spring Boot experience with respect to data processing - near real time, batch based.
- Familiarity with notebook-based environments such as Jupyter Notebook.
- Adaptability: Must be open to learning new technologies and approaches.
- Initiative: Ability to take ownership of tasks, learn independently, and innovate.
- With technology landscape changing rapidly, ability and willingness to learn new technologies as needed and produce results on job.
Preferred Skills:
- Ability to pivot from conventional approaches and develop creative solutions.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
