Job Seekers, Please send resumes to resumes@hireitpeople.com
Must Have Skills (Top 3 technical skills only)*:
- Spark, Hive
- Python, Sqoop
- AWS
Detailed Job Description:
- Advanced experience building cloud scalable, real time and high - performance data lake solutions leveraging AWS, EMR, EC2, S3, Spark, Hive & Lambda
- Experience with relational SQL, preferably Snowflake
- Experience with Python or another scripting language
- Experience with source control tools such as GitHub and related dev process
- Experience with Airflow or another scheduling tool
- Understanding of micro service architecture
- Strong understanding of developing complex data solutions
- Experience working on end-to-end solution design
- Experience preparing data to be analyzed and visualized (preferably with Tableau)
- Experience with Supply Chain a plus
- Experience with Attunity, DMS, Sqoop a plus
- Able to lead others in solving complex problems by taking a broad perspective to identify innovative solutions
- Willing to learn new skills and technologies
- Has a passion for data solutions
- Strong understanding of data structures and algorithms
- Strong understanding of solution and technical design
- Has a strong problem solving and analytical mindset
- Able to influence and communicate effectively, both verbally and written, with team members and business stakeholders
- Able to quickly pick up new programming languages, technologies, and frameworks
Responsibilities you would expect the Subcon to shoulder and execute*:
- Help lead a team of data engineers, architects, and platform engineers to build innovative and sustainable data products that demonstrate business value
- Lead the design and build-out of reusable components, frameworks and libraries at scale to support analytics products
- Lead the design and implementation of product features in collaboration with business and technology stakeholders
- Anticipate, identify and solve issues concerning data management to improve data quality
- Help clean, prepare and optimize data at scale for ingestion and consumption
- Drive the implementation of new data management projects and refactoring of the current data architecture
- Help implement complex automated workflows and routines using workflow scheduling tools
- Lead the build-out of continuous integration, test-driven development and production deployment frameworks
- Drive collaborative reviews of design, code, test plans and dataset implementation performed by other data engineers in support of maintaining data engineering standards
- Analyze and profile data for the purpose of designing scalable solutions
- Troubleshoot complex data issues and perform root cause analysis to proactively resolve product and operational issues
- Mentor and develop data engineers in career development and adopting best practices
