Senior Data Engineer

CTP CONSULTING CORPORATION

Glendale, CA, United States

3 months ago

Role details

Contract type

Temporary contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

5 years minimum

Compensation

$166,400.0 - $187,200.0

Working hours

Regular working hours

Job source

indeed.com

Tech stack

Java (Programming Language) Agile Methodology Airflow Amazon Web Services Big Data Cloud Engineering Computer Programming Continuous Integration Information Engineering Data Governance Data Infrastructure Extract Transform Load (ETL)

+18 more

Data Warehousing Distributed Computing Environment Distributed Systems Python (Programming Language) Online Analytical Processing Online Transaction Processing Workflow Management Systems Data Processing Cloud Platform System Data Ingestion Snowflake Apache Spark Data Lakes Kubernetes Integration Frameworks Data Management Data Pipelines Databricks

Job description

Design, build, and maintain scalable end-to-end data pipelines supporting enterprise data initiatives
Contribute to platform capabilities related to data governance, lineage, privacy, and observability
Work within a modern cloud data ecosystem leveraging tools such as Airflow, Spark, Databricks, Delta Lake, Snowflake, or similar technologies
Collaborate cross-functionally with product, engineering, analytics, and business stakeholders
Establish and promote engineering standards, best practices, and technical documentation
Ensure data quality, performance, scalability, and SLA adherence across datasets and pipelines
Participate in Agile development processes and support CI/CD and automation improvements
Partner with stakeholders to deliver scalable data solutions aligned with evolving business requirements

Requirements

Do you have experience in Scalable systems?, * 7+ years of experience in data engineering, including large-scale data pipeline development

Strong programming skills in Python, Java, or Scala
Advanced SQL expertise and experience with complex data modeling concepts
Hands-on experience with workflow orchestration tools such as Airflow or equivalent
Experience with Databricks/Snowflake, or comparable modern cloud data platforms / data warehouse technologies
Strong understanding of distributed systems, OLTP vs. OLAP architectures, and scalable data processing
Experience working within cloud environments, preferably AWS

Preferred / Nice to Have

Exposure to Kubernetes or containerized deployment environments
Experience with data ingestion/integration tools such as Fivetran, Airbyte, or Matillion
Background in distributed data processing, data platform engineering, or enterprise data services
Familiarity with lakehouse architectures and modern cloud-native data ecosystems, * Data Engineering: 5 years (Required)