Description:

The Data Engineer (The Data Pipeline Architect) role involves designing, building, and maintaining data pipelines that support robust data architectures and facilitate seamless data flow.
The position requires creating scalable solutions that empower data-driven decision-making and developing and optimizing data systems that drive impactful analytics.
Responsibilities include developing and maintaining data pipelines for data ingestion, transformation, and integration using cloud technologies, automating data workflows, and ensuring seamless data movement between systems.
The Data Engineer will manage and optimize data storage solutions, architecting and maintaining data lakes and data warehouses using platforms like BigQuery, Redshift, or Snowflake.
Collaboration with data scientists, analysts, and business stakeholders is essential to understand data requirements and align data solutions with business goals.
The role includes ensuring data quality and reliability through processes for data validation, error handling, and consistency checks.
The Data Engineer will develop and automate ETL processes to handle complex data transformations and monitor and maintain data infrastructure using monitoring tools.
Strategies for efficient resource allocation and cost-effective data processing will be implemented to enhance performance.

Requirements:

Candidates must have experience with cloud data platforms such as AWS, GCP, or Azure, demonstrating proficiency in handling cloud-based data solutions.
Proficiency in programming and scripting languages such as Python, Java, or Scala is required for building data pipelines and processing tasks.
A proven ability to develop, maintain, and optimize ETL processes that handle large volumes of data is essential, along with experience using orchestration tools like Apache Airflow or Luigi.
Strong SQL skills and experience with relational and NoSQL databases are necessary.
Excellent problem-solving skills and a proactive approach to identifying and resolving data-related challenges are required.
A Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field is required, with equivalent experience in data engineering and cloud technologies considered.
Certifications in cloud data engineering are a plus.
Candidates should have 3+ years of experience in data engineering, with a proven track record of building and managing cloud-based data systems.
Experience with real-time data processing frameworks and familiarity with containerization and microservices architecture is advantageous.

Comprehensive medical, dental, and vision insurance plans are offered with low co-pays and premiums.
Competitive vacation, sick leave, and 20 paid holidays per year are provided.
Flexible work schedules and telecommuting options promote work-life balance.
Opportunities for training, certification reimbursement, and career advancement programs are available for professional development.
Access to wellness programs, including gym memberships, health screenings, and mental health resources, is provided.
Life insurance and short-term/long-term disability coverage are included.
Confidential counseling and support services are available through the Employee Assistance Program (EAP).
Financial assistance for continuing education and professional development is offered through tuition reimbursement.
Opportunities to participate in community service and volunteer activities are encouraged.
Employee recognition programs celebrate achievements and milestones.