Big Data Engineers / Leads

Job description

• Actively participate in all phases of the software development lifecycle, including requirements gathering, functional and technical design, development, testing, roll-out, and support.
• Solve complex business problems by utilizing a disciplined development methodology.
• Produce scalable, flexible, efficient, and supportable solutions using appropriate technologies.
• Analyze source and target system data. Map the transformation that meets the requirements.
• Interact with the client and onsite coordinators during different phases of a project.
• Design and implement product features in collaboration with business and technology stakeholders.
• Anticipate, identify, and solve issues concerning data management to improve data quality.
• Clean, prepare, and optimize data at scale for ingestion and consumption.
• Support the implementation of new data management projects and re-structure the current data architecture.
• Implement automated workflows and routines using workflow scheduling tools.
• Understand and use continuous integration, test-driven development, and production deployment frameworks.
• Participate in design, code, test plans, and dataset implementation performed by other data engineers to maintain data engineering standards.
• Analyze and profile data to design scalable solutions.
• Troubleshoot straightforward data issues and perform root cause analysis to resolve product issues proactively.
• Build data lake solutions leveraging one or more of the following AWS, EMR, S3, Hive, and PySpark.

Skills and Experience

• Must have a bachelor s degree in computer science.
• 3+ years of experience in developing data and analytic solutions.
• Expertise in relational SQL, scripting languages such as Python, and working with agile teams.
• Hands-on with source control tools such as GitHub and related development processes.
• Good understanding of workflow scheduling tools such as Airflow.
• In-depth knowledge of AWS cloud (S3, EMR, Databricks).
• Should be passionate about data solutions.
• Strong problem-solving and analytical mindset.
• Thorough with the design, development, and testing of data pipelines.