Associate, Data Engineer

Arevon•Scottsdale, AZ

About The Position

Arevon is recruiting for the position of Associate, Data Engineer, an outstanding opportunity for individuals seeking an exciting, high-growth work environment in one of the most important industries for the 21st century. Our company culture is one where teamwork, adaptability, continuous improvement, achievement of results, and willingness to grow are our core values. The successful candidate will have a superior academic background at a high caliber institution, having exceeded in Engineering or a Mathematical Science Discipline. In addition to superior academic performance, candidates must have enthusiasm for renewable energy.

Requirements

Bachelor’s or Master’s degree in data science, Computer Science, Engineering, Statistics, or a related quantitative field.
5+ years of professional experience in a Data Engineering, Data Scientist or Machine Learning Engineering role specifically focused on building and deploying production data systems.
Mandatory hands-on experience building production data platforms primarily on AWS. Deep familiarity with core AWS services for data ingestion, storage, orchestration, including S3 (primary data lake storage), Lambda (serverless functions), SQS/SNS (event handling and notifications) and CloudWatch (monitoring and alerting.)
Expertise in establishing modern Lakehouse layer built on top of S3, utilizing technology like Databricks / DeltaLake, Snowflake or Redshift.
Expertise in Apache Spark (PySpark, Spark SQL) for processing large, complex datasets with proven ability to tune and optimize spark jobs for cost and performance.
Expert-level proficiency in SQL and demonstrated ability to design schemas and build pipelines optimized for high frequency time-series analytics.
Hands-on experience implementing data governance frameworks, security policies or catalogs in a production cloud environment.
Fluency in Python and common data science libraries like Pandas, NumPy and Scikit-learn.
Experience developing, training and validating anomaly detection models and time-series forecasting models.
Experience writing production-grade code that adheres to software engineering standards, including unit testing, integration testing and peer code reviews.
Expertise in statistical analysis, machine learning, and mathematical modeling.
Proven track record of working well within a team environment, taking ownership of processes and procedures.
Understanding business strategy and the ability to align data insights with organizational goals.
Excellent interpersonal skills, highly motivated and results oriented, process oriented with strong organizational and communication skills.

Responsibilities

Architect and implement scalable, production-ready data pipelines for diverse data types (time-series, structured, unstructured). Establish a cloud-native Data Lakehouse (Databricks / DeltaLake, Snowflake etc) from scratch.
Process and integrate large, diverse datasets from performance data platforms, CMMS platform, and drone inspection imagery and reports into our central data platform for further analytics.
Develop and deploy analytical and predictive models for anomaly detection, root cause analysis, failure prediction and forecast maintenance needs.
Manage the complete data lifecycle, from raw data ingestion into the Bronze layer (e.g. Amazon S3), through cleansing and transformation into Silver layer and finally to the deployment of refined Gold layer data products for advanced analytics, and visualization.
Continuously evaluate software systems, processes, procedures and drive improvement within the performance and operational engineering teams to support Arevon’s growth.
Create and maintain metadata documentation and ensure best practices for data governance and discoverability.