Responsibilities

We are seeking a Data Scientist with strong data engineering capabilities to design, build, and maintain scalable data infrastructure and analytics solutions. This role focuses on developing robust data pipelines, enabling data-driven decision-making, and supporting machine learning and advanced analytics use cases across structured and unstructured data environments. The ideal candidate has strong programming skills, experience working across distributed data systems, and the ability to translate complex technical data problems into reusable, production-ready solutions for stakeholders. Duties & Responsibilities:

Design, build, and maintain scalable data pipelines and infrastructure supporting analytics, reporting, and machine learning use cases

Develop and optimize ETL and ELT workflows for structured and unstructured data sources

Build and maintain data integration layers across cloud, web, and on-premise systems

Ensure data quality, consistency, security, and reliability across data pipelines and storage systems

Develop data processing solutions using Python, SQL, and Bash scripting in Linux environments

Construct and optimize complex queries across multiple data sources (e.g., PostgreSQL, MySQL, Neo4j, RDS)

Develop and manage ingestion pipelines using tools such as Apache NiFi

Process and transform large-scale datasets from diverse structured and unstructured sources

Develop reusable, tested, and reproducible data workflows and Python-based modules

Use Elasticsearch and Kibana for search, indexing, and data visualization use cases

Document technical solutions, data pipelines, and methodologies for both technical and non-technical stakeholders

Communicate findings through written reports, dashboards, and oral briefings to stakeholders

Collaborate across multiple teams to support data-driven decision-making and analytics initiatives

Support knowledge sharing by explaining complex data concepts to junior team members Requirements:

Strong experience in data engineering and data pipeline development, including ETL/ELT design and implementation

Proficiency in Python programming for data processing and automation

Strong experience with SQL and relational database systems

Experience working in Linux environments with advanced Bash scripting

Experience building and managing data pipelines using Apache NiFi or similar tools

Experience processing both structured and unstructured data sources

Experience working with Elasticsearch and Kibana

Experience using Git-based version control systems

Experience using Jupyter Notebooks for analysis and prototyping

Experience delivering technical results through documentation and stakeholder briefings

Strong Communication Skills And Experience Working With Multiple Stakeholders

Experience creating reusable, tested, and maintainable data solutions

Academic or professional background in math, statistics, physics, computer science, data science, or related fields Preferred Qualifications:

Experience with cloud platforms such as AWS and cloud-based data architectures

Experience with big data processing frameworks such as Apache Spark or Trino

Experience applying machine learning algorithms and NLP techniques

Experience with containerization technologies such as Docker or Kubernetes

Experience with data visualization tools such as Tableau, Kibana, or Apache Superset

Experience working with or designing machine learning workflows and models

Experience creating training materials or technical curriculum in data or scientific domains

Familiarity with data science MLOps or production ML workflows What we offer: Flexible time off

Full medical coverage

401(k) with company match

Referral bonuses

Performance bonuses

Life insurance and disability coverage

Tuition and training reimbursement