Role overview

Data Engineer (Elasticsearch + Datawarehousing)

Requirements and responsibilities

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Data Engineer (Elasticsearch + Data warehousing)

  • Design, implement, and optimize Elasticsearch clusters for high-performance querying and data retrieval.
  • Build and manage Elasticsearch indexes, ensuring data is stored, indexed, and queried efficiently.
  • Build and optimize data storage solutions like data lakes and warehouses.
  • Integrate structured and unstructured data from various internal and external systems to create a unified view for analysis.
  • Ensure data accuracy, consistency, and completeness through rigorous validation, cleansing, and transformation processes.
  • Maintain comprehensive documentation for data processes, tools, and systems while promoting best practices for efficient workflows.

Requirements Gathering and Analysis

  • Collaborate with product managers, and other stakeholders to gather requirements and translate them into technical solutions.
  • Participate in requirement analysis sessions to understand business needs and user requirements.
  • Provide technical insights and recommendations during the requirements-gathering process.

Agile Development

  • Participate in Agile development processes, including sprint planning, daily stand-ups, and sprint reviews.
  • Work closely with Agile teams to deliver software solutions on time and within scope.
  • Adapt to changing priorities and requirements in a fast-paced Agile environment.

Testing and Debugging

  • Conduct thorough testing and debugging to ensure the reliability, security, and performance of applications.
  • Write unit tests and validate the functionality of developed features and individual elements.
  • Writing integration tests to ensure different elements within a given application function as intended and meet desired requirements.
  • Identify and resolve software defects, code smells, and performance bottlenecks.

Continuous Learning and Innovation

  • Stay updated with the latest technologies and trends in full-stack development.
  • Propose innovative solutions to improve the performance, security, scalability, and maintainability of applications.
  • Continuously seek opportunities to optimize and refactor existing codebase for better efficiency.
  • Stay up-to-date with cloud platforms such as AWS, Azure, or Google Cloud Platform.

Collaboration

  • Collaborate effectively with cross-functional teams, including testers, and product managers.
  • Foster a collaborative and inclusive work environment where ideas are shared and valued.

Skills and Experience We Value:

  • Bachelor's degree in Computer Science, Engineering, or related field.
  • Proven experience as a Data Engineer, with a minimum of 3 years of experience.
  • Proficiency in Elasticsearch and Python programming language is a must.
  • Experience with database technologies such as SQL (e.g., MySQL, PostgreSQL) and NoSQL (e.g., MongoDB) databases.
  • Strong understanding of Programming Libraries/Frameworks and technologies such as Flask, API frameworks, Data warehousing/lakehouse, Principles, Database, ORM, Data analysis, Databricks, Pandas, Spark, PySpark, Machine learning, OpenCV, Scikit-learn.
  • Utilize Java to build and enhance backend systems, particularly for integration with Elasticsearch and databases.
  • Develop APIs, microservices, and automation scripts as needed.
  • Utilities & Tools: logging, requests, subprocess, regex, pytest
  • ELK stack, Redis, distributed task queues
  • Strong understanding of data warehousing/lakehousing principles and concurrent/parallel processing concepts.
  • Familiarity with at least one cloud data engineering stack (Azure, AWS, or GCP) and the ability to quickly learn and adapt to new ETL/ELT tools across various cloud providers.
  • Familiarity with version control systems like Git and collaborative development workflows.
  • Competence in working on Linux OS and creating shell scripts.
  • Solid understanding of software engineering principles, design patterns, and best practices.
  • Excellent problem-solving and analytical skills, with a keen attention to detail.
  • Effective communication skills, both written and verbal, and the ability to collaborate in a team environment.
  • Adaptability and willingness to learn new technologies and tools as needed.

Skills and Experience We Value:

  • E - Empowering: Enabling individuals to reach their full potential.
  • L - Leadership: Taking initiative and guiding each other toward success.
  • I - Innovation: Embracing creativity and new ideas to stay ahead.
  • T - Teamwork: Collaborating with empathy to achieve common goals.
  • E - Excellence: Striving for the highest quality in everything we do.
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FocusData EngineeringRole area
Seniority signalMiddleCandidate level
StackAWS, Azure, GCPPrimary skills
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