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Senior Data Engineer
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Senior Data Engineer
Plano, TX (Hybrid onsite 2 days a week)
6+ Month Contract
As the Senior Data Engineer for a Fortune 50 company, you will be responsible for day-to-day data collection, transportation, maintenance, and access to enterprise data within data management & operations organization. You will work with a team of data engineers to build data pipelines and develop large & complex data applications into public cloud environments.
MINIMUM QUALIFICATIONS
- Bachelor’s degree in Computer Science, Computer Engineering, Technology, Information Systems (CIS/MIS), Engineering or related technical discipline or equivalent experience/training.
- 6+ years of overall technology experience that includes at least 4+ years of hands-on software development, data engineering, and systems architecture.
- 4+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools.
- 4+ years of experience in SQL optimization and performance tuning, and development experience in programming languages like Python, PySpark, Scala etc.).
- 2+ years in cloud data engineering experience in Azure.
- Fluent with Azure cloud services. Azure Certification is a plus.
- Experience with integration of multi cloud services with on-premises technologies.
- Experience with data modeling, data warehousing, and building high-volume ETL/ELT pipelines.
- Experience with data profiling and data quality tools like Apache Griffin, Deequ, and Great Expectations.
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets.
- Experience with at least one MPP database technology such as Redshift, Synapse or SnowFlake.
- Experience with running and scaling applications on the cloud infrastructure and containerized services like Kubernetes.
- Experience with version control systems like Github and deployment & CI tools.
- Experience with Azure Data Factory, Azure Databricks and Azure Machine learning tools.
- Experience with Statistical/ML techniques is a plus.
- Experience with building solutions in the retail or in the supply chain space is a plus
- Understanding of metadata management, data lineage, and data glossaries is a plus.
- Working knowledge of agile development, including DevOps and DataOps concepts.
- Familiarity with business intelligence tools (such as PowerBI).
RESPONSIBILITES:
- Active contributor to code development in projects and services.
- Manage and scale data pipelines from internal and external data sources to support new product launches and drive data quality across data products.
- Build and own the automation and monitoring frameworks that captures metrics and operational KPIs for data pipeline quality and performance.
- Responsible for implementing best practices around systems integration, security, performance and data management.
- Empower the business by creating value through the increased adoption of data, data science and business intelligence landscape.
- Collaborate with internal clients (data science and product teams) to drive solutioning and POC discussions.
- Providing technical guidance and code reviews to colleagues
- Evolve the architectural capabilities and maturity of the data platform by engaging with enterprise architects and strategic internal and external partners.
- Develop and optimize procedures to “productionalize” data science models.
- Define and manage SLA’s for data products and processes running in production.
- Support large-scale experimentation done by data scientists.
- Prototype new approaches and build solutions at scale.
- Research in state-of-the-art methodologies.
- Create documentation for learnings and knowledge transfer.
- Create and audit reusable packages or libraries.