Dice is the leading career destination for tech experts at every stage of their careers. Our client, Javen Technologies, Inc, is seeking the following. Apply via Dice today!
What we are looking for:
- 10+ years overall work experience and bachelor s degree in information science, Computer Science, Mathematics, Statistics or a quantitative discipline in science, business, or social science.
- Hands-on engineer who is curious about technology, should be able to quickly adopt to change and one who understands the technologies supporting areas such as Cloud Computing (AWS, Azure(preferred), etc.), Micro Services, Streaming Technologies, Network, Security, etc.
- 3 or more years of active development experience as a data developer using Python-spark, Spark Streaming, Azure SQL Server, Cosmos DB/Mongo DB, Azure Event Hubs, Azure Data Lake Storage, Azure Search etc.
- Team player, Reliable, self-motivated, and self-disciplined individual capable of executing on multiple projects simultaneously within a fast-paced environment working with cross functional teams
- 5+ years of experience working with source code control systems and Continuous Integration/Continuous Deployment tools
- Independent and able to manage, prioritize & lead workload
- Experience with big data technologies like Apache Spark, and distributed computing frameworks using databricks, EMR, Glue or HD Insight.
- Familiarity with data modeling concepts, database systems (relational and NoSQL), and data governance practices.
- Strong analytical and problem-solving skills.
Senior Data Engineer:
- Develop systems that ingest, cleanse and normalize diverse datasets, develop data pipelines from various internal and external sources and build structure for previously unstructured data.
- Identify performance bottlenecks in the data pipelines, ETL processes, and queries, and propose and implement optimization strategies to improve overall system performance.
- Define and implement data architecture best practices, ensuring the scalability, availability, and security of data infrastructure, including data lakes, data warehouses, and related components.
- Collaborate with data scientists and analysts to design and implement data models that support complex analytical and reporting requirements.
- Conduct data profiling, validation, and quality checks to ensure data integrity and consistency.
- Unify, enrich, and analyze variety of data to derive insights and opportunities
- Optimize data extraction, transformation, and loading processes (ETL) to enable smooth and timely ingestion of large volumes of structured and unstructured data from various sources.
- Develop POCs to influence platform architects, product managers and software engineers to validate solution proposals and migrate
- Develop and maintain documentation related to data flows, data dictionaries, data lineage, and data integration processes.
- Contribute and adhere to CI/CD processes, development best practices and strengthen the discipline in Data Engineering Org