Key skills
Data EngineeringPythonETL/ELT pipelinesData WarehousingData VisualizationMachine LearningBig Data TechnologiesContainerizationDevOps PracticesCommunication SkillsMentorshipCollaborationPyTorchTensorFlowETLELTAnalyticsLookerBITableauPower BISnowflakeBigQueryRedshiftDatabricksSparkApache SparkKafkaAirflowHadoopStatistical AnalysisAWSKubernetesDockerGlueGitVersion ControlCI/CDLeadershipMentoringCommunication
About this role
MojoTech is an innovative digital consulting company that integrates strategy, design, and engineering to create results-driven digital products and experiences for clients nationwide. As a Data & Analytics Engineer, you will work with clients to solve complex problems and deliver high-quality solutions, leading discussions to define data requirements and deliver actionable insights and data pipelines to support client analytics needs.
Responsibilities:
- Collaborating with product managers, designers, and clients to define data requirements
- Delivering actionable insights and data pipelines to support client analytics needs
Requirements:
- 3+ years of experience in Data Engineering, Data Science, Data Warehousing
- Strong experience in Python
- Experience building and maintaining ETL/ELT pipelines, data warehouses, or real-time analytics systems
- BA/BS in Computer Science, Data Science, Engineering, or a related field or equivalent experience in data engineering or analytics
- Track record of developing and optimizing scalable data solutions and larger-scale data initiatives
- Strong understanding of best practices in data management, including sustainment, governance, and compliance with data quality and security standards
- Commitment to continuous learning and sharing knowledge with the team
- Experience developing solutions using LLMs (RAG, Agents, etc...)
- Exposure to big data technologies like Hadoop, Kafka, or Flink for handling large-scale data processing
- Experience with data visualization tools such as Tableau, Power BI, or Looker to communicate insights effectively
- Knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch) or statistical analysis for predictive analytics
- Familiarity with containerization and orchestration tools like Docker and Kubernetes in a data engineering context
- Understanding of DevOps practices, including CI/CD pipelines and version control systems (e.g., Git)
- Previous work with real-time data streaming or event-driven architectures
- Comfort collaborating with cross-functional teams, including data scientists, analysts, and software engineers
- Experience one or more of the following: Palantir, Databricks, Snowflake, Apache Spark, Airflow, AWS Redshift, AWS Glue, Google BigQuery, Google Dataflow, PowerBI, etc
- Exposure to leadership or mentorship roles, particularly on a development team
- Experience working in an agency, as a software consultant, or tailoring solutions to match client requirements and capability
- Strong communication skills to articulate technical concepts to technical and non-technical stakeholders
- Experience mentoring team members or leading small projects is a plus
- Located in RI, MA, CT, NY, NJ, NC, SC, FL, CO, CA, UT, OR, PA, TN