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Urgent! Head of Data Engineering and Analytics Job Opening In India, India – Now Hiring Confidential
Must have skills required :
DBT, GCP, DWH, Data Modelling, Data Governance, data quality, data monitoring, Cost Management
Good to have skills :
Multi Cloud
Forbes Advisor (One of Uplers' Clients) is Looking for:
Senior Data Architect who is passionate about their work, eager to learn and grow, and who is committed to delivering exceptional results.
If you are a team player, with a positive attitude and a desire to make a difference, then we want to hear from you.
Role Overview Description
Company Description
Forbes Advisor, part of the Forbes Marketplace family, provides consumers with
expert-written insights, news, and reviews on personal finance, health, business, and
everyday life decisions.
We empower our audience with data-driven knowledge so
they can make informed choices confidentlybalancing the agility of a startup with
the stability of a seasoned enterprise
Role Overview
The Senior Data Architect is a strategic, senior leadership role responsible for
setting the vision and direction of our data warehousing function.
You will architect,
implement, and maintain a state-of-the-art data warehouse that drives actionable
insights across revenue, subscriptions, paid marketing channels, and operational
functions.
Your leadership will ensure data quality, robust pipeline design, and
seamless integration with business intelligence tools.
This role requires a strong mix
of technical acumen, team management, and cross-functional collaboration
especially with teams focused on SEM, Digital Experiences, and revenue attribution
Job Description
Key Responsibilities
Strategic Data Architecture & Pipeline Leadership
Vision & Strategy:
Define and execute the long-term strategy for our data warehousing
platform using medallion architecture (Bronze, Silver, Gold layers) and
modern cloud-based solutions.
End-to-End Pipeline Oversight:
Oversee data ingestion (via Google Ads, Bing Ads, Facebook Ads, GA,
APIs, SFTP, etc.), transformation (leveraging DBT, and SQL [via
BigQuery]), and reporting, ensuring that our pipelines are robust and
scalable.
Data Modeling Best Practices:
Champion best practices in data modeling, including the effective use
of DBT packages to streamline complex transformations.
Data Quality, Governance & Attribution
Quality & Validation:
Establish and enforce rigorous data quality standards, governance
policies, and automated validation frameworks across all data streams.
Standardization & Visibility:
Collaborate with the Data Engineering, Insights and BIOps team to
standardize data definitions (including engagement metrics and
revenue attribution) and ensure consistency across all reports.
Attribution Focus:
Develop frameworks to reconcile revenue discrepancies and unify
validation across Finance, SEM, and Analytics teams.
Ensure accurate attribution of revenue and paid marketing channel
performance, working closely with SEM and Digital Experiences teams.
Monitoring & Alerting:
Implement robust monitoring and alerting systems (e.g., Slack and
email notifications) to quickly identify, diagnose, and resolve data
pipeline issues.
Team Leadership & Cross-Functional Collaboration
People & Process:
Lead, mentor, and grow a high-performing team of data warehousing
specialists, fostering a culture of accountability, innovation, and
continuous improvement.
Stakeholder Engagement:
Partner with RevOps, Analytics, SEM, Finance, and Product teams to align
the data infrastructure with business objectives.
Serve as the primary data warehouse expert in discussions around
revenue attribution and paid marketing channel performance, ensuring
that business requirements drive technical solutions.
Communication:
Translate complex technical concepts into clear business insights for
both technical and non-technical stakeholders.
Operational Excellence & Process Improvement
Deployment & QA:
Oversee deployment processes, including staging, QA, and rollback
strategies, to ensure minimal disruption during updates.
Continuous Optimization:
Regularly assess and optimize data pipelines for performance,
scalability, and reliability while reducing operational overhead.
Legacy to Cloud Transition:
Lead initiatives to transition from legacy on-premise systems to
modern cloud-based architectures for improved agility and cost
efficiency.
Innovation & Thought Leadership
Emerging Trends:
Stay abreast of emerging trends and technologies in data warehousing,
analytics, and cloud solutions.
Pilot Projects:
Propose and lead innovative projects to enhance our data capabilities,
with a particular focus on predictive and prescriptive analytics.
Executive Representation:
Represent the data warehousing function in senior leadership
discussions and strategic planning sessions
Qualifications
Education & Experience
Technical Expertise
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Great news! Confidential is currently hiring and seeking a Head of Data Engineering and Analytics to join their team. Feel free to download the job details.
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