Senior Data Engineer - (No Benchsales/No OPT / No-H1B) - Fulltime

Job Description

Skill: IT Security Engineer

Must Have Technical/Functional Skills:

Objective of Role:

• This role is responsible for leading complex efforts to develop and deliver complex data solutions to accomplish cyber security technology and business goals.
• Key responsibilities include code design and delivery tasks associated with the integration, cleaning, transformation, and control of data in operational and analytics data systems.
• They guide stakeholders, Product Owners, and Software Engineers through the design and execution processes.
• These individuals provide technical thought leadership based on the significant experience they have built through implementing multiple complex data solutions, and their knowledge of the interaction across multiple data flows and systems.
• The candidate is expected to have knowledge in the cyber security domain.
• Primary Level of Engagement: Works as a team member under supervision from a more senior domain expert.

Primary Interactions:

• Business partners and stakeholders
• Product Owner
• Scrum Master
• Development Team
• Feature Lead
• Architect
• Domain Community of Practice
• Data Scientists

Required Skills:

• Minimum 8+ years hands-on data engineer/Software development exp (at least 5 years of onsite exp)
• Experience with big data processing systems like Hadoop, Cloudera etc
• Experience with one or more of the programming languages like Python (Modular python programming exp)
• Strong SQL and UNIX experience
• Hadoop – Hive, Spark , Pispark

• Proven experience with technology leadership guiding junior engineers towards project completion and deliveries
• Experience with cyber security domain, preferably vulnerability data management
• 8+ years of hands-on data engineer/software development
• Ability to switch from technology leadership to hands on coding when required
• Experience with big data processing systems like Hadoop, Cloudera, etc.
• Experience with Cloud Services\Technologies like AWS, Azure, etc.
• Experience with one or more of the programming languages like Python
• Strong SQL and UNIX experience
• Experience with data stores like HIVE, HBase Elastic
• Experience with code versioning systems like Bitbucket
• Experience with CICD pipelines
• Good knowledge on Data engineering principles and SDLC process
• Ability to detect early and articulate with business partners the challenges and gaps in requirements

· Experience: Minimum 8+ years

Roles & Responsibilities:

• Ensure that the design and engineering approach for complex data solutions is consistent across multiple flows and systems.
• Conduct research, designs prototyping and other exploration activities such as evaluating new toolsets.
• Utilize multiple architectural components in design and development of client requirements.
• Maintain, improve, clean and manipulate data for the operational and/or analytics data systems.
• Constantly looking for better ways of solving technical problems and designing the solution without being afraid of challenging the status quo.
• Collaborate with development teams to understand data requirements and ensure the data architecture is feasible to implement and subsequently implemented accurately.
• Assemble large, complex data sets that meet functional/ non-functional requirements.
• Build processes supporting data transformation, data structures, metadata, data quality controls, dependency and workload management.
• Define and build data pipelines that enable faster, better, data-informed decision-making within the business.
• Contribute to existing test suites (integration, regression, performance), analyze test reports, identify any test issues/errors, and triage the underlying cause.
• Document and communicate required information for deployment, maintenance, support, and business functionality.
• Adhere to team delivery/release process and cadence pertaining to code deployment and release
• Identify gaps in data management standards adherence and work with appropriate partners to develop plans to close gaps.
• Lead concept and experimentation testing, and synthesize the results to validate and improve analytical solution.
• Define key performance indicators and internal controls.
• Mentor more junior Data Engineers and coach team members in the delivery/release CI-CD events – (for example, branching timelines, pull requests, issue triage, merge/conflict resolution, and release notes).