[Hiring] Senior Data Engineer @Consensus Cloud Solutions

Role Description

The Senior Data Engineer will be responsible for designing and building the infrastructure to aggregate data from multiple sources for reporting and analytics.

• Design, develop, and maintain a robust data infrastructure to support data-driven decisions.
• Lead the development of scalable data processing pipelines and build data sets from unstructured data.
• Manage all aspects of the data and analytics systems from stream configuration to ETL/ELT to aggregate tables and cubes for reporting and analytical needs.
• Serve as a player/coach, leading and mentoring a team of data professionals by providing guidance and support to achieve objectives.
• Perform data analysis.
• Perform other duties and responsibilities as required, assigned, or requested.

Qualifications

• 5+ years of experience in data engineering, backend infrastructure or software development.
• Bachelor's degree in Computer Science, Engineering or a Quantitative related field.

Requirements

• Familiarity with semantic layers in data architecture.
• Cloud and data stack familiarity: Azure, Google and AWS.
• Experience with ETL/ELT design and development, and OLAP tools to support business applications.
• Acquiring and preparing data from disparate sources.
• Data quality management.
• Expertise with API design, build, implementation and maintenance.
• Building and maintaining data lakes/lakehouses and ingestion pipelines (files, CDC, streaming).
• Practical experience in data governance (policies, standards, stewardship, DQ rules, issue management).
• Strong change management record (training, communications, adoption, stakeholder alignment).
• Comprehend core business and financial concepts, including financial statements and SaaS KPIs.
• Ability to successfully work independently and collaborate interdepartmentally.
• Cross-functional leadership and influencing skills.
• Strategic vision with operational execution discipline.
• Strong problem-solving and critical thinking skills.
• In-depth knowledge of data architecture, including data modeling, warehousing principles, and the development of efficient data transformation pipelines.
• Expertise in designing and deploying scalable data solutions using SQL and Python, with a focus on data transformation, automation and analytics.
• Extensive experience with modern data platforms and tools, particularly Databricks and Airflow, with a demonstrated ability to harness their full capabilities.
• Knowledge of standard engineering productivity tools such as Github, JIRA, Confluence, etc.
• Data warehousing solutions (e.g., Snowflake, Redshift, BigQuery).
• Experience with scheduling tools (e.g., Airflow or Composer).
• BI tools Tableau and PowerBI.
• Automate manual processes, monitor system performance, troubleshoot issues, and continually optimize data infrastructure for efficiency and reliability.
• Using AI to facilitate automated pipeline creation, data cleaning and monitoring to scale and optimize processes.

Benefits

• The salary range for this role is $175,000-$190,000 USD annually.
• The total compensation package for this position is negotiable and may also include annual performance bonus, ESPP, enhanced time off packages and benefits.

Additional Details

• Location requirements: Fully remote within the U.S. (Los Angeles or Las Vegas preferred).
• Travel requirements: Up to 10% travel.
• Physical requirements: Must be able to sit for long periods, as well as handle long periods of screen time.
• Technology requirements: Reliable, high speed internet.
• Eligible for sponsorship: No.