Sr Data Engineer

Air Methods•Greenwood Village, CO

About The Position

The Senior Data Engineer at Air Methods is responsible for leading and growing our data-driven decision culture by designing, developing, and delivering data engineering and analytical solutions that are customer focused, easy to consume and create business impact. To be successful, this teammate must have a passion for mentoring other data engineers and working with stakeholders to understand their needs and deliver value through the entire data pipeline. You will design and implement complex data models, model metadata, build data pipelines, reports and dashboards, and own data presentation and dashboarding tools for the end users of our data products and systems. You will write scalable, highly tuned SQL queries and will develop learning and training programs to drive adoption of data driven decision making across the organization.

Requirements

Bachelor’s degree (BS/BA) from four-year college or university in Information Computer Science or related field, and eight+ years’ related experience and/or training; or equivalent combination of education and experience
10+ years in Data Engineering or related field
5+ years working in a cloud computing environment, Azure preferred
Extensive experience in building scalable data platforms in a cloud data platform, Snowflake preferred
Extensive experience gathering data from multiple heterogeneous data sources, including databases, various file formats, and REST and SOAP APIs
Hands-on experience with Azure technologies, such as SQL and NoSQL databases, Azure DevOps, Azure Data Factory, Databricks, and Azure Analytics Services desired
Strong experience with Data Visualization Tools (Power BI preferred)
Strong experience in an Agile Scrum environment, with work estimation and providing input to managers on resource and risk planning
Ability to lead and mentor other data engineers
Authoritative in ELT optimization, designing, coding, and tuning data processes
Experience with building data pipelines and applications to stream and process datasets at low latencies
Experience in data mining, profiling, and analysis
Experience with complex data modelling, ELT design, and using large databases in a business environment
Demonstrates efficiency in handling data - tracking data lineage, ensuring data quality, and improving discoverability of data
Affinity for learning modern technologies, data analysis, and identifying data patterns and trends
Proven ability to develop unconventional solutions; Sees opportunities to innovate and leads the way
Demonstrates high critical thinking and reasoning skills and strong attention to detail while working in a fast-paced environment that requires ability to prioritize and multi-task
Excellent communication skills, both written and verbal
Advanced experience with Microsoft Suite, including Word, Excel, PowerPoint, and Outlook
Experience modeling data in cloud data platforms such as Snowflake, Redshift, and or BigQuery
Experience with Python, Spark and PySpark desired
Expert in data architecture, ELT, and data ingestion development skills
Advanced proficiency in writing complex SQL statements and manipulating large structured and semi-structured datasets.
Experience with scheduling tools or a DAG scheduler
Experience with cloud warehouse ELT tools (e.g., Matillion, dbt)

Responsibilities

Develop and improve the current data architecture, emphasizing data security, data quality and timeliness, scalability, and extensibility
Develop and implement complex and efficient data pipelines/solutions to transform raw data sources into powerful, reliable components of our data platform and business insights
Deploy and use various data and big data technologies and run pilots to design low latency data architectures at scale
Implement and simplify self-service data query and analysis capabilities of the data platform
Establish and maintain standards and guidelines for design and development, tuning, deployment, and maintenance of information and advanced data analytics
Meet with subject matter experts in different areas of the business, be able to quickly learn the concepts and business language relevant to their line of business and develop an understanding of how their data supports their business processes
Actively mentor and lead knowledge sharing sessions, code, and design reviews
Build conceptual and logical data models for stakeholders and management
Actively lead knowledge sharing sessions, code, and design reviews
Support the data platform infrastructure and implement solutions to ensure continuous improvement in platform stability
Collaborate with business analysts, data scientists, product owners, software development engineers, and other teams to develop, implement, and validate KPIs, statistical analyses, data profiling, prediction, forecasting, clustering, and machine learning algorithms
Other duties as assigned