Senior Data Engineer

Job Description

At Cloudera, we empower people to transform complex data into clear and actionable insights. With as much data under management as the hyperscalers, we're the preferred data partner for the top companies in almost every industry. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world’s largest enterprises.

Cloudera Data Engineers are key contributors to Cloudera's Data Platform, responsible for ingesting, curating, and provisioning data to support Business Operations, Analytics and AI / ML initiatives. In this role, you'll design and implement data pipelines, utilizing a broad array of Big Data and Cloud based technologies to manage complex data ingestion and transformation workflows with diverse requirements and SLAs. These pipelines support complex machine learning workflows and business intelligence systems.

As a Cloudera Data Engineer, you will deepen your expertise in data ingestion and transformation, while ensuring the quality and integrity of data pipelines. You’ll work in an agile development environment, creating flexible and reusable pipelines based on the specifications provided by Data, Business Intelligence and Operations Architects. The data you provide will be instrumental in guiding the actions of business teams across the organization.

A successful candidate will contribute to building robust data management processes on Cloudera's native Data Platform. These processes will support internal analytics and serve as models to drive external customer success.

Key Responsibilities :

Collaborate with Data Architects, Operational Architects, and Data Analysts to understand the data and operational requirements across different business units.

Partner with data owners to ensure seamless, reliable data ingestion.

Develop and implement data transformations to enrich and provision data, following established specifications and standards.

Create real-time, near real-time, and point-in-time data flows to meet the operational demands of business systems.

Implement monitoring processes to track data quality and ensure the reliability of data services.

Requirements :

5+ years of experience as a Data Engineer.

Strong communication skills, both written and verbal.

Proficient in coding with SQL, scripting languages, Python, SPARK, and Java.

Experience with ETL, Business Intelligence, and Data Processing.

Proven track record of contributing to the architecture and implementation of reliable data pipelines.

Experience building data models using industry best practices (e.g., Kimball, Inmon).

Hands-on experience with Hadoop technologies, including at least one of Impala, Hive, Kafka, MapReduce, or Spark.

Ability to monitor critical data pipelines for quality and resolve any issues effectively.

Nice to Have :

Experience with Apache Airflow or Apache NiFi.

Expertise in optimizing data storage using HDFS / Parquet / Avro, Kudu, or HBase.

Experience developing data engineering processes to support AI / ML use cases.

What you can expect from us :

Generous PTO Policy

Support work life balance with

Flexible WFH Policy

Mental & Physical Wellness programs

Phone and Internet Reimbursement program

Access to Continued Career Development

Comprehensive Benefits and Competitive Packages

Employee Resource Groups

EEO / VEVRAA