Cloud Data Scientist: Big Data & ETL Analytics

Bespoke Technologies, Inc.; Chantilly (VA); On-site; USD 120,000 - 150,000; Full time

Job summary

Bespoke Technologies, Inc. in Chantilly seeks a Data Scientist to support customer requirements, extend and maintain bulk data pipelines, and enhance analytics across multiple cloud-based applications.

The role focuses on building scalable data flows, processing logs, and delivering dashboards and reports for stakeholders. Ideal candidates have hands-on experience with Spark, PySpark, Python, SQL and ETL, plus exposure to analytics tools like CloudWatch and Kibana.

Qualifications

• Experience with big data processing using Spark, PySpark and Python.
• Experience in data mapping, extraction, transformation, and loading.
• Experience building analytic reports in CloudWatch and Kibana.
• Experience converting OS and data logs into reports and dashboards.
• Familiar with regex for text extraction and pattern matching.
• Proficient with SQL databases (MySQL/PostgreSQL).
• Experience processing XML/JSON data formats.
• Experience with notebooks and data modeling in IDEs like Visual Studio.
• Experience ETL-ing disparate data into structured, indexed formats.
• Experience data quality analysis and documentation.

Responsibilities

• Support customer requirements for new system capabilities.
• Extend and maintain bulk data pipelines across applications.
• Enhance data processing in the customer's cloud environment.
• Collaborate with stakeholders to clarify objectives and deliverables.
• Assist Agile teams with tasking definition and scope review.

Skills

Spark

PySpark

Python

SQL

ETL

Data mapping

Data quality analysis

Dashboards/Reports

Regex

Tools

Databricks

Elastic Stack (ELK)

CloudWatch

Kibana

Notebooks

Visual Studio

Job description

Bespoke Technologies, Inc. in Chantilly seeks a Data Scientist to support customer requirements, extend and maintain bulk data pipelines, and enhance analytics across multiple cloud-based applications.

The role focuses on building scalable data flows, processing logs, and delivering dashboards and reports for stakeholders. Ideal candidates have hands-on experience with Spark, PySpark, Python, SQL and ETL, plus exposure to analytics tools like CloudWatch and Kibana.