Data Engineer (Experienced)
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Job Category Products and Technology
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The team is made up of data scientists, engineers, growth analysts, and information management experts who are dedicated to driving product strategy with data-driven insights. The team works with executives, product managers, designers, developers, user researchers, marketers, and sales strategy team members across all Cloud businesses to discover new opportunities for growth and optimization, experiment with data, drive adoption, and provide actionable insights that impact product strategy.
The Data Engineer position will be responsible for designing, developing & maintaining all parts of the data pipeline to build interactive and curated data needed to drive insights through data science, reporting & analytics. The role requires to partner with Data Scientists, Software Engineers, Data Analysts, and Information Management experts within Salesforce. This role involves making an impact by driving continuous improvements in moving, aggregating, profiling, sampling, testing and analyzing terabytes of data.
- Own the technical solution design, lead the technical architecture and implementation of data acquisition and integration projects, both batch and real time. Define the overall solution architecture needed to implement a layered data stack that ensures a high level of data quality and timely insights.
- Communicate with product owners and analysts to clarify requirements. Craft technical solutions and assemble design artifacts (functional design documents, data flow diagrams, data models, etc.).
- Build data pipelines data processing tools and technologies in open source and proprietary products.
- Serve the team as a subject matter expert & mentor for ETL design, and other related big data and programming technologies.
- Identify incomplete data, improve quality of data, and integrate data from several data sources.
- Proactively identify performance & data quality problems and drive the team to remediate them. Advocate architectural and code improvements to the team to improve execution speed and reliability.
- Design and develop tailored data structures in database and Hadoop.
- Quickly create functioning ETL prototypes to address quickly changing business needs.
- Revamp prototypes to create production-ready data flows.
- Support Data Science research by designing, developing, and maintaining all parts of the Big Data pipeline for reporting, statistical and machine learning, and computational requirements.
- Perform data profiling, complex sampling, statistical testing, and testing of reliability on data.
- Clearly articulate pros and cons of various technologies and platforms in open source and proprietary products. Execute proof of concept on new technology and tools to help the organization pick the best tools and solutions.
- Harness operational excellence & continuous improvement with a can do leadership attitude.
- BS/MS degree in Computer Science, Engineering, Mathematics, Physics, or equivalent/related degree.
- 5+ years of experience working with ETL tools, specifically creating data driven orchestration and transformation jobs and user and project administration. A strong Python scripting knowledge including hands-on experience in building packages for ETL is required. Advanced Matillion developer is a plus.
- 4+ years of experience with Data Warehouse including knowledge of Stored Procedures, tasks and streams. Must be an expert in writing complex SQL queries and understand the methodologies to tune/improve query performance.
- Previous projects should display technical leadership with an emphasis on data lake, data warehouse solutions, business intelligence, big data analytics, enterprise-scale custom data products.
- Familiarity with new big data management techniques of schema on read, search analytics, graph analytics, semantic data lakes, linked data, etc.
- Knowledge of data modeling techniques and high-volume ETL/ELT design.
- Strong SQL optimization and performance tuning experience in a high volume data environment that utilizes parallel processing. Hadoop, Spark, Teradata platform experience a plus.
- Experience with version control systems (Github, Subversion) and deployment tools (e.g. continuous integration) required.
- Experience with programming languages like Java, Scala & scripting in Python, Perl, Bash.
- Experience working with Public Cloud platforms like GPC, AWS, or Azure.
- Familiarity with scrum/agile project management methodologies and SDLC stages required.
- Hands-on on Salesforce.com knowledge of product and functionality a plus.
- Ability to work effectively in an unstructured and fast-paced environment both independently and in a team setting, with a high degree of self-management with clear communication and commitment to delivery timelines.
- Strong problem solving with acute attention to detail and ability to meet tight deadlines and project plans.
- Ability to research, analyze, interpret, and produce accurate results within reasonable turnaround times with an iterative mindset with rapid prototyping designs.
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