AWS Data Lake Engineer

Overview

Remote
Accepts corp to corp applications
Contract - Independent
Contract - W2
Contract - 1 day((s))

Skills

SQL
AWS
Python
data lake

Job Details

Role : AWS Data Lake Engineer

Location : Remote (Quarterly travel to Seattle)

Position and Project Overview and Description:

Client is looking to fill a temporary contracted assignment for a highly skilled AWS Data Engineer to design, build, and optimize large-scale data pipelines and analytics solutions on Amazon Web Services (AWS). The ideal candidate will have strong expertise in cloud-based data engineering, hands-on experience with AWS native services, and a solid understanding of data lake, data warehouse, and real-time streaming architectures.

The Data Engineer will support Client's data lake implementation. The role will design and build the infrastructure and pipelines that enable organizations to collect, store, process, and analyze large volumes of structured and unstructured data efficiently and securely. A Data Engineer is responsible for the end-to-end data lifecycle, from ingestion and transformation to storage and delivery for analytics, machine learning, and operational systems. They ensure data is reliable, high-quality, scalable, and accessible for business and technical stakeholders.

The expectation is that this resource will be 100% utilization for a duration of eight months (mid-October 2025 July 2026). Continuing work will be assessed on an as-needed basis.

Specific position responsibilities

Data Pipeline, Integration and Transformation Development

  • Design, build, and optimize ETL/ELT workflows to ingest data from multiple sources. (e.g., S3, Redshift, Lake Formation, Glue).
  • Implement data cleansing, enrichment, and standardization processes.
  • Automate batch and streaming data pipelines for real-time analytics. Build solutions for both streaming (Kinesis, MSK, Lambda) and batch processing (Glue, EMR, Step Functions).
  • Ensure pipelines are optimized for scalability, performance, and fault tolerance.
  • Optimize SQL queries, data models, and pipeline performance.
  • Ensure efficient use of cloud-native resources (compute, storage, networking).

Data Architecture and Storage

  • Design and implement data architecture across data lakes, data warehouses, and lakehouses.
  • Optimize data storage strategies (partitioning, indexing, schema design).
  • Implement data integration from diverse sources (databases, APIs, IoT, third-party systems).

Collaboration

  • Work with Data Scientists, Analysts, and BI developers to deliver clean, well-structured data.
  • Document data assets and processes for discoverability.
  • Training of existing core staff who will maintain infrastructure and pipelines.

Required Qualifications

  • Bachelor's degree in Computer Science, Data Engineering, or related field.
  • 3 7+ years of experience in data engineering roles
  • Proficiency in SQL, Python, or Scala for data transformation and processing.
  • Experience in the utility industry data
  • Strong understanding of utility data domains: meter data, customer data, grid/asset data, work management, outage data.
  • Familiarity with CIM standards and utility integration frameworks.
  • Working Knowledge of AWS services such as:
  • Storage & Processing: S3, Glue, Redshift, Athena, EMR
  • Streaming: Kinesis, MSK, Lambda
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.