Senior Data Engineer - Quicksight

Job Description

About Quantiphi:

\n

Quantiphi is an award-winning, AI-First global digital engineering company that helps the world’s leading Fortune 1000 organizations transform bold ideas into measurable business impact. We go beyond building innovative AI technologies—we solve the problems that matter most to our clients.

\n

\n

Since our founding in 2013, Quantiphi has built a proven track record of turning complex challenges into meaningful outcomes across industries.

\n

\n

Headquartered in Boston, with more than 4,000 professionals worldwide, we partner with global enterprises to deliver large-scale digital, cloud, and AI-driven transformation. #SolvingWhatMatters.

\n

\n

We are an Elite and Premier partner to Google Cloud, AWS, NVIDIA, Snowflake, and other leading technology platforms, and our work has been recognized across the industry, including:

\n

\n
• 21 Google Cloud Partner of the Year awards in the past 10 years
\n
• 3 AWS AI/ML Partner of the Year awards
\n
• 3 NVIDIA Partner of the Year awards
\n
• 3 Snowflake Partner of the Year awards
\n
• Rated Leaders by Gartner, Forrester, IDC, ISG, Everest Group and other leading analyst firms
\n

\n

\n

Quantiphi delivers First-in-class AI solutions across Life Sciences, Healthcare, Banking, Financial Services, CPG, Manufacturing, Energy, High-Tech, Telecommunications, etc., powered by cutting-edge Generative AI and Agentic AI accelerators.

\n

\n

We are also proud to be certified as a Great Place to Work—reflecting our commitment to our people and our culture.

\n

\n

For more details, visit: Website or LinkedIn Page

\n

\n

Role: Senior Data Engineer - Quicksight

\n

Experience Level: 7+ years

\n

Employment type: Full Time

\n

Location: Remote (USA)

\n

\n

Basic Qualifications (BQ):

\n

\n
• Hands-on experience in building and maintaining scalable and cost-effective data pipelines, data warehouses and data lake using AWS S3, AWS Glue/Amazon EMR, AWS Lambda to ingest data from various sources (e.g., APIs, databases, flat files, etc.).
\n
• Expertise in implementing data modeling and data warehousing concepts to create a well-structured analytical layer on top of the data lake, optimized for querying with AWS Redshift and AWS Athena.
\n
• Proficiency in SQL (complex joins, window functions, query optimization) and strong programming skills in Python/PySpark for data processing and automation.
\n
• Ensure data quality, integrity, and reliability by implementing robust monitoring, alerting, and validation frameworks for all data pipelines.
\n
• Solid understanding of data modeling concepts (e.g., star/snowflake schemas, SCD) and data warehousing principles.
\n
• Hands-on experience with Amazon QuickSight, with a strong understanding of the latest features and capabilities.
\n
• Ability to understand business requirements and translate them into scalable dashboards, including KPIs, tooltips, user interactions, dashboard navigation, personas, access management, and reporting requirements.
\n
• Strong experience in:
\n
• SPICE optimization
\n
• Direct Query
\n
• Data blending
\n
• Custom visual creation
\n
• Calculated fields and parameters
\n
• Experience implementing Row-Level Security (RLS) and other security controls within QuickSight.
\n
• Ability to independently design, develop, test, and deploy production-grade QuickSight dashboards.
\n
• Validate dashboard functionality, KPI calculations, and data accuracy against business requirements.
\n
• Experience documenting dashboard design, implementation, testing, validations, and deployment activities.
\n
• Ability to optimize queries, datasets, and visualizations for performance and scalability.
\n
• Experience developing and maintaining datasets and data models for Amazon QuickSight and other BI platforms.
\n
• Ability to gather reporting requirements from business stakeholders and convert them into meaningful dashboards and visualizations.
\n
• Strong verbal and written communication skills with the ability to communicate effectively with both business and technical teams.
\n

\n

\n

Preferred Qualifications (PQ):

\n

\n
• Experience with workflow orchestration tools like AWS Step Functions or Apache Airflow.
\n
• Experience managing QuickSight assets, including publishing dashboards, scheduling refreshes, user administration, and access management.
\n
• Experience with Tableau or Power BI.
\n
• Proven experience migrating dashboards and reports from BI platforms such as Qlik, Tableau, or Power BI to Amazon QuickSight.
\n
• Experience monitoring and supporting analytics solutions in AWS environments.
\n

\n

\n

What is in it for you:

\n

\n
• Join one of the world’s fastest-growing AI-first digital engineering companies and make a real impact at scale.
\n
• Lead and collaborate with a high-energy team of talented, driven individuals solving complex, meaningful challenges.
\n
• Work with Fortune 500 companies and disruptive innovators in a research-driven environment with 60+ patents.
\n
• Stay ahead of the curve by gaining hands-on experience with cutting-edge AI, ML, data, and cloud technologies while continuously upskilling.
\n

\n