SID Global Solutions
Sr Global Talent Acquisition Lead @ SID Global Solutions
Job Title: Business Intelligence Engineer
Location: Austin, TX (Onsite)
Employment Type: Full-time
Overview We are seeking a highly skilled
business- and Operations-Oriented BI Engineer
to join our
Warehouse Automation Analytics
team. This role focuses on
designing, developing, and maintaining data pipelines, dashboards, and AI-powered reporting solutions
that drive operational excellence across fulfilment centres.
The ideal candidate is a
self-starter
with a
research mindset
— capable of taking high-level goals, translating them into actionable analytics initiatives, and executing independently. You will play a key role in leveraging
AWS Cloud, QuickSight, RDS (MySQL/MariaDB), and Python
to enable data-driven decision‑making within
retail logistics and warehouse operations .
Responsibilities
Design, develop, and maintain
ETL pipelines
using
AWS Glue
to integrate data from multiple systems into
Amazon Redshift .
Build, optimize, and automate
interactive dashboards and reports
in
Amazon QuickSight
to support leadership and business stakeholders.
Develop and maintain
data connectors and APIs
for seamless integration across internal systems.
Leverage
Amazon Q (GenAI)
for report summarization, insights generation, and conversational analytics within QuickSight.
Collaborate with
data engineers, full‑stack developers, product owners, and business analysts
to translate business requirements into actionable metrics.
Define, measure, and monitor
key performance indicators (KPIs)
related to warehouse readiness, utilization, downtime, and cost variance.
Identify process gaps and propose
AI‑driven improvements
to enhance productivity, accuracy, and reporting capabilities.
Participate in
end‑to‑end solution development
— from data ingestion and modeling to visualization and insights delivery.
Ensure
data quality, governance, and scalability
across the analytics ecosystem.
Translate
operational and logistics goals
into measurable BI outcomes.
Required Skills
AWS Cloud
ecosystem: Redshift, Glue, QuickSight, S3, Lambda, and
RDS (MySQL or MariaDB) .
Strong experience in
SQL ,
ETL development , and
data modeling .
Proficiency in
Python
or
PySpark
for data transformations and automation.
Hands‑on experience with
BI tools
(QuickSight, Power BI, Tableau, etc.).
Familiarity with
AI/ML integration
and
LLM‑based tools
(Amazon Q, ChatGPT, Gemini).
Strong
business and operational understanding , especially within
retail logistics and warehouse operations .
Solid understanding of
data warehouse architecture
and
report automation .
Excellent analytical, problem‑solving, and communication skills with the ability to work
independently .
What You’ll Bring
A
business‑first mindset
with strong
operational awareness
to connect data insights to tangible outcomes.
A
research‑driven, self‑motivated approach
to exploring new methods, tools, and frameworks.
Ability to
work cross‑functionally
and communicate effectively with both technical and non‑technical stakeholders.
Curiosity and drive to
innovate within the GenAI + Data Engineering space , improving analytics maturity and automation.
Benefits
Medical insurance
Vision insurance
401(k)
#J-18808-Ljbffr
Location: Austin, TX (Onsite)
Employment Type: Full-time
Overview We are seeking a highly skilled
business- and Operations-Oriented BI Engineer
to join our
Warehouse Automation Analytics
team. This role focuses on
designing, developing, and maintaining data pipelines, dashboards, and AI-powered reporting solutions
that drive operational excellence across fulfilment centres.
The ideal candidate is a
self-starter
with a
research mindset
— capable of taking high-level goals, translating them into actionable analytics initiatives, and executing independently. You will play a key role in leveraging
AWS Cloud, QuickSight, RDS (MySQL/MariaDB), and Python
to enable data-driven decision‑making within
retail logistics and warehouse operations .
Responsibilities
Design, develop, and maintain
ETL pipelines
using
AWS Glue
to integrate data from multiple systems into
Amazon Redshift .
Build, optimize, and automate
interactive dashboards and reports
in
Amazon QuickSight
to support leadership and business stakeholders.
Develop and maintain
data connectors and APIs
for seamless integration across internal systems.
Leverage
Amazon Q (GenAI)
for report summarization, insights generation, and conversational analytics within QuickSight.
Collaborate with
data engineers, full‑stack developers, product owners, and business analysts
to translate business requirements into actionable metrics.
Define, measure, and monitor
key performance indicators (KPIs)
related to warehouse readiness, utilization, downtime, and cost variance.
Identify process gaps and propose
AI‑driven improvements
to enhance productivity, accuracy, and reporting capabilities.
Participate in
end‑to‑end solution development
— from data ingestion and modeling to visualization and insights delivery.
Ensure
data quality, governance, and scalability
across the analytics ecosystem.
Translate
operational and logistics goals
into measurable BI outcomes.
Required Skills
AWS Cloud
ecosystem: Redshift, Glue, QuickSight, S3, Lambda, and
RDS (MySQL or MariaDB) .
Strong experience in
SQL ,
ETL development , and
data modeling .
Proficiency in
Python
or
PySpark
for data transformations and automation.
Hands‑on experience with
BI tools
(QuickSight, Power BI, Tableau, etc.).
Familiarity with
AI/ML integration
and
LLM‑based tools
(Amazon Q, ChatGPT, Gemini).
Strong
business and operational understanding , especially within
retail logistics and warehouse operations .
Solid understanding of
data warehouse architecture
and
report automation .
Excellent analytical, problem‑solving, and communication skills with the ability to work
independently .
What You’ll Bring
A
business‑first mindset
with strong
operational awareness
to connect data insights to tangible outcomes.
A
research‑driven, self‑motivated approach
to exploring new methods, tools, and frameworks.
Ability to
work cross‑functionally
and communicate effectively with both technical and non‑technical stakeholders.
Curiosity and drive to
innovate within the GenAI + Data Engineering space , improving analytics maturity and automation.
Benefits
Medical insurance
Vision insurance
401(k)
#J-18808-Ljbffr