Consensus Cloud Solutions is a leading digital cloud fax and interoperability solutions organization focused on connecting healthcare providers and technology innovators. The Senior Data Engineer will design and build data infrastructure to support analytics, manage data systems, and lead a team of data professionals.
Responsibilities:
- The role involves designing, developing and maintaining a robust data infrastructure to support data-driven decisions
- Supporting the finance team, this position will lead the development of scalable data processing pipelines and building data sets from unstructured data
- This position will 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
- Serving 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. Consensus reserves the right to add or change duties at any time
Requirements:
- 5+ years of experience in data engineering, backend infrastructure or software development
- 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
- Bachelor's degree in Computer Science, Engineering or a Quantitative related field