Overall Purpose
The Data Engineer evaluates, designs, and develops business intelligence solutions across multiple technology stacks. They work closely across multiple business functions and technology partners to interpret metrics into information clarity that informs planning, measuring, trending and enhanced operational performance. They research technology best-practices, implement frameworks, and align BI directions with strategic business initiatives. Analyze metrics sources, monitor data quality, define logical inter-dependencies, develop datamarts and build comprehensive business process dashboards.

Essential Functions

• Work with business users to define new and existing requirements for reports and dashboards as well as identify gaps in data, logic, and business understanding
• Design and develop backend solutions for new data sources using Cloudera technology stack
• Using Tableau, create complex, visually appealing, and interactive dashboards/ scorecards/ reports to support business processes, including related trends, and projections
• Conduct in-depth data analysis to come up with logical results and perform cause and effect analysis based on the data available.
• Design data ETL and manipulations to support production and ad-hoc analyses and reports
• Investigate industry best-practices and help guide strategic data platforms, tools, and processes
• Recommends standards, policies and procedures for the form, structure, and attributes of the BI tools and systems
• Provides support and training to business teams as necessary
• Write data infrastructure & analytics software tools for Data Science.
• Mentor and train interns.
• Guide Data Scientists on best practices in software engineering.
• Collaborate with analytics leadership and engineers from other parts of EW on architectural and software enhancements to the Data Science platform.
• Collaborate with Data Science leadership on improving ETL and cluster computing.
• Supporting the company's commitment to risk management and protecting the integrity and confidentiality of systems and data

Minimum Qualifications

• Education and experience typically obtain through a Bachelor's degree
• Typically has 2-4 years of demonstrated progressive work experience in the following - PySpark/Python/Spark/Scala in a Linux environment for Data Engineering development
• Understanding of Tableau Server and Tableau Dashboard
• Demonstrated ability with testing, problem solving and analysis
• Knowledge of the principle, practices and techniques of dashboard development, reporting, data modeling, ETL and systems design
• Experience working with SQL Spark
• Software/data engineering in Python
• Machine Learning toolkits in Python/R
• Building reusable frameworks for data ingestion and storage in Hadoop or AWS/S3
• Relational databases, optimizing/tuning queries, indexing, partitioning, etc.
• Experience collaborating with internal engineering & technology teams within a company on building data infrastructure in a regulated, enterprise environment;
• Strong communication skills
• Background and drug screen

Preferred Qualifications
• Prior demonstrated experience 2-4 years
• Scala/Java PySpark experience
• Experience with Hive/Impala & Linux
• Fin-tech experience

The above job description is not intended to be an all-inclusive list of duties and standards of the position.

Physical Requirements
Working conditions consist of a normal office environment. Work is primarily sedentary and requires extensive use of a computer and involves sitting for periods of approximately four hours. Work may require occasional standing, walking, kneeling and reaching. Must be able to lift 10 pounds occasionally and/or negligible amount of force frequently. Requires visual acuity and dexterity to view, prepare, and manipulate documents and office equipment including personal computers. Requires the ability to communicate with internal and/or external customers.

Employee must be able to perform essential functions and physical requirements of position with or without reasonable accommodation.

The base pay scale for this position in:
Phoenix, AZ/ Chicago, IL in USD per year is: $83,000 - $110,000.
New York, NY/ San Francisco, CA in USD per year is: $99,000 - $132,000.
Additionally, candidates are eligible for a discretionary incentive plan and benefits.

This pay scale is subject to change and is not necessarily reflective of actual compensation that may be earned, nor a promise of any specific pay for any specific candidate, which is always dependent on legitimate factors considered at the time of job offer. Early Warning Services takes into consideration a variety of factors when determining a competitive salary offer, including, but not limited to, the job scope, market rates and geographic location of a position, candidate's education, experience, training, and specialized skills or certification(s) in relation to the job requirements and compared with internal equity (peers). The business actively supports and reviews wage equity to ensure that pay decisions are not based on gender, race, national origin, or any other protected classes.

Some of the Ways We Prioritize Your Health and Happiness

• Healthcare Coverage - Competitive medical (PPO/HDHP), dental, and vision plans as well as company contributions to your Health Savings Account (HSA) or pre-tax savings through flexible spending accounts (FSA) for commuting, health & dependent care expenses.
• 401(k) Retirement Plan - Featuring a 100% Company Safe Harbor Match on your first 6% deferral immediately upon eligibility.
• Paid Time Off - Flexible Time Off for Exempt (salaried) employees, as well as generous PTO for Non-Exempt (hourly) employees, plus 11 paid company holidays and a paid volunteer day.
• 12 weeks of Paid Parental Leave
• Maven Family Planning - provides support through your Parenting journey including egg freezing, fertility, adoption, surrogacy, pregnancy, postpartum, early pediatrics, and returning to work.

And SO much more! We continue to enhance our program, so be sure to check our Benefits page here for the latest. Our team can share more during the interview process!