Data Science Advisor

Jobtailor; Washington (District of Columbia); On-site; USD 120,000 - 170,000; Full time

Job summary

Jobtailor is seeking a senior data engineering professional to design, build, and scale foundational data infrastructure in a Washington DC area setting. You will architect Data Lakes and Data Warehouses in the cloud, and guide data platform decisions across contracts.

The role requires deep data engineering knowledge, strong AWS security, and hands-on design of scalable pipelines using Spark, Kafka, and Kinesis. Local DC residency is expected, with ability to communicate risk to executives.

Qualifications

• 8 years of experience with a BS/BA, 6 years with a MS/MA, or 3 years with a PhD, or 12 years of experience in lieu of a degree.
• Active Secret clearance required.
• Strong expertise in AWS architecture and security in the SDLC.
• Ability to communicate technical risk and architecture decisions to executive audiences.
• Experience designing and building Data Lakes, Data Warehouses, and scalable data platforms in the cloud.
• Programming skills in Java, SQL, Scala, Python, and R.
• Defining schema and software engineering best practices including secure, testable, and maintainable code and database design (e.g., SQL, NoSQL, Hadoop, Spark, Kafka, Kinesis).
• Deep understanding of data engineering principles and techniques.
• Ability to work effectively in teams, in both a lead and support role.
• Ability to learn new techniques and troubleshoot code without support.
• Must be local to the Washington DC Metro area.

Responsibilities

• Design, build, and scale an organization’s foundational data infrastructure.
• Design and build Data Lakes, Data Warehouses, and scalable data platforms in the cloud.
• Support technical activities across the contract.
• Drive continuous improvement and innovation into program operations.
• Advise on technology alternatives related to processing, data storage, data access, application development, and enterprise architecture decisions.
• Establish coding best practices and align complex data architectures with overarching business goals.
• Use APIs to push and pull data from various data systems and platforms.
• Build and optimize ETL/ELT pipelines using Glue and Python.
• Package, curate, and version datasets for LM fine‑tuning and model training jobs on Bedrock and SageMaker.
• Enforce CUI handling requirements, automate PII detection, and maintain audit trails (e.g., Amazon Macie).

Skills

AWS architecture

Data engineering

Java

SQL

Scala

Python

R

Hadoop

Spark

Kafka

Kinesis

NoSQL

Data Lakes

Data Warehouses

Security in SDLC

Executive communication

PII handling

Team leadership & collaboration

Active Secret clearance

Education

BS/BA in a related field

MS/MA in a related field

PhD in a related field

12+ years of experience in lieu of a degree

Tools

AWS Glue

Bedrock

SageMaker

Amazon Macie

Kinesis

Kafka

Spark

Hadoop

Job description

Responsibilities

• Design, build, and scale an organization’s foundational data infrastructure.
• Design and build Data Lakes, Data Warehouses, and scalable data platforms in the cloud.
• Support technical activities across the contract.
• Drive continuous improvement and innovation into program operations.
• Advise on technology alternatives related to processing, data storage, data access, application development, and enterprise architecture decisions.
• Establish coding best practices and align complex data architectures with overarching business goals.
• Use APIs to push and pull data from various data systems and platforms.
• Build and optimize ETL/ELT pipelines using Glue and Python.
• Package, curate, and version datasets for LM fine‑tuning and model training jobs on Bedrock and SageMaker.
• Enforce CUI handling requirements, automate PII detection, and maintain audit trails (e.g., Amazon Macie).

Requirements

• 8 years of experience with a BS/BA, 6 years with a MS/MA, or 3 years with a PhD, or 12 years of experience in lieu of a degree.
• Active Secret clearance.
• Strong expertise in AWS architecture and security in the SDLC.
• Ability to communicate technical risk and architecture decisions to executive audiences.
• Experience designing and building Data Lakes, Data Warehouses, and scalable data platforms in the cloud.
• Programming skills in Java, SQL, Scala, Python, and R.
• Defining schema and software engineering best practices including secure, testable, and maintainable code and database design (e.g., SQL, NoSQL, Hadoop, Spark, Kafka, Kinesis).
• Deep understanding of data engineering principles and techniques.
• Ability to work effectively in teams, in both a lead and support role.
• Ability to learn new techniques and troubleshoot code without support.
• Must be local to the Washington DC Metro area.