What are the responsibilities and job description for the Data Engineer position at Jobs via Dice?
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Hiring: W2 Candidates Only
Visa: Open to any visa type with valid work authorization in the USA
Key Responsibilities:
Hiring: W2 Candidates Only
Visa: Open to any visa type with valid work authorization in the USA
Key Responsibilities:
- Assemble large, complex data sets that meet functional and non-functional business requirements.
- Identify, design, and implement process improvements, including automation, data delivery optimization, and infrastructure redesign for scalability.
- Lead and deliver data-driven solutions across multiple languages, tools, and technologies.
- Contribute to architecture discussions, solution design, and strategic technology adoption.
- Build and optimize highly scalable data pipelines incorporating complex transformations and efficient code.
- Design and develop new source system integrations from varied formats (files, database extracts, APIs).
- Design and implement solutions for delivering data that meets SLA requirements.
- Work with operations teams to resolve production issues related to the platform.
- Apply best practices such as Agile methodologies, design thinking, and continuous deployment.
- Develop tooling and automation to make deployments and production monitoring more repeatable.
- Collaborate with business and technology partners, providing leadership, best practices, and coaching.
- Mentor peers and junior engineers; educate colleagues on emerging industry trends and technologies.
- Bachelor's degree in Computer Science, Software Engineering, or related field, or equivalent experience
- 7 years of data engineering/development experience, including Python or Scala, SQL, and relational/non-relational data storage. (ETL frameworks, big data processing, NoSQL)
- 3 years of experience in distributed data processing (Spark) and container orchestration (Kubernetes)
- Proficiency in data streaming in Kubernetes and Kafka
- Experience with cloud platforms - Azure preferred; AWS or Google Cloud Platform also considered.
- Solid understanding of CI/CD principles and tools
- Familiarity with big data technologies such as Hadoop, Hive, HBase, Object Storage (ADLS/S3), Event Queues.
- Strong understanding of performance optimization techniques such as partitioning, clustering, and caching
- Proficiency with SQL, key-value datastores, and document stores
- Familiarity with data architecture and modeling concepts to support efficient data consumption
- Strong collaboration and communication skills; ability to work across multiple teams and disciplines.
- Master's degree in Computer Science, Software Engineering, or related field
- Knowledge of data governance, metadata management, or data quality/observability
- Familiarity with schema design and data contracts
- Experience handling various file formats (video, audio, image)
- Experience with Databricks, Snowflake, or similar platforms
- Experience designing and implementing robust data ingestion frameworks for heterogeneous data sources (structured/unstructured files, external suppliers, supplier chain systems).
