Senior Data Engineer

UNAVAILABLE; McLean (VA); On-site; USD 120,000 - 180,000; Full time

Job summary

Senior Data Engineer role in McLean, VA to develop enterprise grade data platforms, services, and pipelines for clients. You will lead architecture, migrations, and optimization with a focus on performance, reliability, and scalability.

The ideal candidate has 5–7 years in data engineering, deep AWS, Hadoop/Spark, SQL/NoSQL experience, and strong communication in an Agile setting.

Qualifications

• 5-7 years industry experience coding commercial software and a passion for solving complex problems.
• 5-7 years direct experience in Data Engineering with experience in tools such as Hadoop, Spark, Kafka, etc.
• Advanced working SQL knowledge and experience with relational databases, query authoring and optimization (SQL).
• Experience architecting data systems (transactional and warehouses) and data modeling.

Responsibilities

• Lead and architect migration of data environments with performance and reliability.
• Assess and understand the ETL jobs, workflows, BI tools, and reports
• Address technical inquiries concerning customization, integration, enterprise architecture and general feature / functionality of data products
• Experience in crafting database / data warehouse solutions in cloud (AWS preferred)
• Support an Agile software development lifecycle
• Contribute to the growth of our Data Exploitation Practice!

Skills

Python

AWS

Big data

Hadoop

Spark

Kafka

SQL

NoSQL

Airflow

Spark-Streaming

Solr

Lucene

Elasticsearch

Postgres

Cassandra

Java

Scala

Python

Education

Baccalaureate or higher in Computer Science or related field

Tools

Azkaban

Luigi

Airflow

Oozie

Storm

Kafka

Hadoop

Spark

Lucene

Elasticsearch

Job description

Overview

We are looking for seasoned Senior Data Engineer to work with our team and our clients to develop enterprise grade data platforms, services, and pipelines.We are looking for more than just a \"Senior Data Engineer\", but a technologist with excellent communication and customer service skills and a passion for data and problem solving.

Responsibilities

• Lead and architect migration of data environments with performance and reliability.
• Assess and understand the ETL jobs, workflows, BI tools, and reports
• Address technical inquiries concerning customization, integration, enterprise architecture and general feature / functionality of data products
• Experience in crafting database / data warehouse solutions in cloud (Preferably AWS. Alternatively Azure, GCP).
• Key must have skill sets - Python, AWS
• Support an Agile software development lifecycle
• You will contribute to the growth of our Data Exploitation Practice!

Qualifications

• Ability to hold a position of public trust with the US government.
• 5-7 years industry experience coding commercial software and a passion for solving complex problems.
• 5-7 years direct experience in Data Engineering with experience in tools such as:
  • Big data tools: Hadoop, Spark, Kafka, etc.
  • Relational SQL and NoSQL databases, including Postgres and Cassandra.
  • Data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
  • AWS cloud services: EC2, EMR, RDS, Redshift (or Azure equivalents)
  • Data streaming systems: Storm, Spark-Streaming, etc.
  • Search tools: Solr, Lucene, Elasticsearch
  • Object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
• Advanced working SQL knowledge and experience working with relational databases, query authoring and optimization (SQL) as well as working familiarity with a variety of databases.
• Experience with message queuing, stream processing, and highly scalable 'big data' data stores.
• Experience manipulating, processing, and extracting value from large, disconnected datasets.
• Experience manipulating structured and unstructured data for analysis
• Experience constructing complex queries to analyze results using databases or in a data processing development environment
• Experience with data modeling tools and process
• Experience architecting data systems (transactional and warehouses)
• Experience aggregating results and/or compiling information for reporting from multiple datasets
• Experience working in an Agile environment
• Experience supporting project teams of developers and data scientists who build web-based interfaces, dashboards, reports, and analytics/machine learning models