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Data Engineer III

1 month ago

Seattle, United States Intelliswift Full time

Pay rate range - $76/hr. to $79/hr. on W2
Hybrid 3 days in office

Must Have
AWS Cloud services
Data Engineering
Python or Scala

REQUIRED SKILLS

  • Looking for Sr. Data engineer
  • Very comfortable with Data modelling, data warehousing ETL, Scripting. Orchestration, Data Pipeline, Taxonomy
  • Python, Scala or Spark, SQL
  • Looking for someone who is already AWS cloud services like S3, lambda, glue, EMR, Lake formation, step function, ec2
  • Experience with AWS services with minimum 2 years is a Must

Years of Experience: 5+ years of experience

Degree or Certification:
  • BS in Computer science or Statistics or engineering
  • Masters Preferred
  • Data Engineer Certification
  • AWS certification
Key job responsibilities
  • As a Data Engineer, your pivotal role will revolve around designing, building, and maintaining robust data pipelines and infrastructure to drive data-driven insights.
  • Core responsibilities include architecting scalable and fault-tolerant pipelines to extract, transform, and load data from various sources into data warehouses or lakes.
  • Leveraging cutting-edge tools and technologies, you'll implement ingestion, transformation, and integration processes, ensuring stringent data quality through validation, cleansing, and deduplication.
  • You'll design and implement high-performance, scalable, and cost-efficient data storage solutions.
  • Utilizing CI/CD principles, you'll automate infrastructure deployment and maintenance processes, ensuring a streamlined data ecosystem.
  • Data modeling and engineering will be crucial, involving designing and implementing optimized data models, developing and maintaining ETL processes, and collaborating with analysts and functional managers to understand data needs and provide tailored data structures.
  • Ensuring data governance, security, and compliance will be paramount.
  • You'll implement robust policies and processes, enforce access controls, encryption, and auditing mechanisms, and collaborate cross-functionally to establish and maintain data governance standards.
  • Continuous improvement and automation will be woven into your daily activities, continuously evaluating and optimizing processes, pipelines, and infrastructure, implementing automation and monitoring tools, and staying ahead of emerging data engineering technologies and trends.

    Basic qualifications
  • 5+ years of data engineering, database engineering, business intelligence, or business analytics experience
  • Bachelor's degree in computer science, engineering, analytics, mathematics, statistics, IT, or equivalent
  • Knowledge of distributed systems as it pertains to data storage and computing
  • Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
  • Proficient in programming languages such as Python, Scala, or Java, and familiarity with SQL.
  • Experience with data engineering tools and frameworks like Apache Spark, Apache Kafka, Apache Airflow, or similar.
  • Knowledge of data warehousing concepts, dimensional modeling, data modeling techniques and building ETL pipelines.
  • Strong problem-solving and analytical skills, with the ability to translate business requirements into technical solutions.
  • Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams.

Preferred Qualifications
  • Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
  • Experience with business intelligence and visualization software (e.g., Quicksight.) to develop dashboards that are used by senior leadership.
  • Experience working with technical and non-technical, internal customers to drive their own analytics and reporting (self-serve reporting) and support ad-hoc reporting when needed.
  • Experience building world-class data environments with a high emphasis on data quality and data security.