About the role

  • Analytics Engineer building data pipelines, ML models, and PowerBI at Mars United Commerce. Supporting data governance, ETL/ELT, and client-facing analytics initiatives.

Responsibilities

  • Develop and maintain data pipelines and ETL processes
  • Optimize data infrastructure for efficient data processing
  • Ensure data quality and accessibility for data scientists and analysts
  • Collaborate with cross-functional teams to address data needs and challenges
  • Implement data governance and security best practices
  • Support annual planning initiatives with clients
  • Work closely with cross-functional teams, including analysts, product managers and domain experts to understand business requirements, formulate problem statements, and deliver relevant data science solutions
  • Develop and optimize machine learning models by processing, analyzing and extracting data from varying internal and external data sources
  • Develop supervised, unsupervised, and semi-supervised machine learning models using state-of-the-art techniques to solve client problems
  • Show up - be accountable, take responsibility, and get back up when you are down
  • Make stuff
  • Share so others can see what’s happening
  • Establish and create scalable and intuitive reporting methodologies through Power BI, suggesting the best representation and visualizations
  • Identify business intelligence needs recommending the best KPIs and customer valuation models and dashboards
  • Interpret data, analyze results, and identify trends or patterns in complex data sets
  • Filter and “clean” data and review computer reports, printouts, and performance indicators to locate and correct data corruption problems
  • Automate data pipelines and develop automation workflows
  • Develop Single Customer View stitching 1P data from various data sources

Requirements

  • A bachelor’s/master’s degree in data analytics, computer science, or a directly related field
  • 3-5 years of industry experience in a data analytics or related role
  • Proficiency in SQL for data querying and manipulation
  • Experience with data warehousing solutions
  • Design, implement, and manage ETL workflows to ensure data is accurately and efficiently collected, transformed, and loaded into our data warehouse
  • Proficiency in programming languages such as Python and R
  • Experience with cloud platforms such as AWS, Azure, and Google Cloud
  • Experience in developing and deploying machine learning models
  • Knowledge of machine learning engineering practices, including model versioning, deployment, and monitoring
  • Familiarity with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn)
  • Ability to design and develop scalable data pipelines for batch and real-time data processing
  • Experience with big data technologies such as Apache Spark, Hadoop, or similar
  • Proficiency in working with structured and unstructured data sources
  • Knowledge of data governance and security best practices
  • Strong understanding of data modeling techniques and best practices
  • Experience with DevOps or MLOps practices for continuous integration and deployment
  • Establish and create scalable and intuitive reporting methodologies through Power BI, suggesting the best representation and visualizations
  • Identify business intelligence needs recommending the best KPIs and customer valuation models and dashboards
  • Interpret data, analyze results, and identify trends or patterns in complex data sets
  • Filter and “clean” data and review computer reports, printouts, and performance indicators to locate and correct data corruption problems
  • Data collection, setting and leveraging DMP and CDP-based infrastructures, attribution modeling, A/B & multivariate testing, and dynamic creative
  • Develop, evaluate, test, and maintain architectures and data solutions such as ETL Pipelines, Data Warehouses, Data Marts, etc
  • Automate data pipelines and develop automation workflows
  • Develop scalable and intuitive ETL & ELT pipelines from a variety of marketing sources such as Salesforce, Adobe Analytics, etc
  • Identify data sources and create data pipelines using shell scripts or Python scripts
  • Create technical documentation
  • Plan data analysis work and develop execution estimates, continuously improving the accuracy of the estimates
  • Develop Single Customer View stitching 1P data from various data sources

Benefits

  • comprehensive group health plans
  • a parental leave program that includes paid maternity and paternity benefits for pregnancy, adoption and surrogacy
  • flexible paid time off
  • a broad and confidential employee assistance program
  • ongoing wellness support initiatives
  • trusted financial health advice and guidance
  • promotion of education through tuition support and assistance
  • a flexible and supportive work environment and culture
  • Temporary roles may be eligible to participate in our freelancer/temporary employee medical plan through a third-party benefits administration system once certain criteria have been met
  • Temporary roles may also qualify for participation in our 401(k) plan after eligibility criteria have been met
  • For regular roles, the Company will offer medical coverage, dental, vision, disability, 401k, and paid time off.

Job title

Analytics Engineer

Job type

Experience level

Mid levelSenior

Salary

$72,390 - $90,440 per year

Degree requirement

Bachelor's Degree

Location requirements

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