Strategic Marketing Data & Analytics Analyst

Fairygodboss

Pittsburgh (Allegheny County)

On-site

USD 90,000 - 130,000

Full time

8 days ago

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Job summary

PNC is seeking a Portfolio Analytics & Strategy Analyst to join the Marketing and Customer Analytics Data Enablement team in the US. You will build and maintain data pipelines powering marketing intelligence, collaborating with analysts, data scientists, and business stakeholders to translate data needs into scalable solutions.

You will work on data modeling, data quality, governance, and performance optimization to enable data-driven decisions in marketing campaigns while adhering to banking

Qualifications

2+ years of experience as a Data Analyst, with a strong preference for experience in a marketing or financial services context.
Strong proficiency in Python, SQL and Spark is essential, with the ability to leverage AI tools like GitHub Copilot to debug, create code validations, and write readme files.
Hands-on experience with visualization platforms like Tableau or PowerBI.
Hands-on experience with data engineering project management and documentation tools such as Atlassian Jira and Confluence.
Hands-on experience with modern cloud data warehouses like Snowflake, Big Query, or Amazon Redshift.
Experience building and managing ETL/ELT pipelines using tools like Apache Airflow, or similar technologies.
Experience with at least one major cloud provider (AWS, or Azure).
Solid understanding of data modeling principles (e.g., star schema, snowflake schema).
Excellent problem-solving skills and attention to detail.
Strong communication and interpersonal skills, with the ability to explain complex technical concepts to non-technical stakeholders.
A proactive and collaborative attitude, with a passion for building data solutions that deliver real business value.
Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
Experience with real-time data streaming technologies (e.g., Kafka, Kinesis).
Familiarity with marketing platforms and their APIs (e.g., Adobe Experience Platform, Salesforce Marketing Cloud, Google Ads).
Knowledge of machine learning concepts and experience building data pipelines for ML models.
Familiarity with financial industry regulations and data security best practices.

Responsibilities

Design & Development: Build, test, and maintain robust data pipelines and ETL/ELT processes to ingest, transform, and load data from various sources into our data warehouse.
Data Modeling: Design and implement efficient data models that support reporting, ad-hoc analysis, and ML initiatives.
Infrastructure Management: Design, manage and optimize data infrastructure including data warehouses, data lakes, and orchestration tools like Airflow.
Data Quality & Governance: Ensure data accuracy, consistency, and reliability; monitor pipelines and maintain governance practices.
Performance Optimization: Optimize queries and data structures for faster data access for analysts and data scientists.
Collaboration: Partner with cross-functional teams to ensure data handling is secure and compliant with banking regulations.
Innovation: Stay current with data engineering technologies and propose improvements to the data platform.
Leverages business/product expertise to analyze large datasets, improve risk-adjusted returns, and support growth and decision-making.
Develops and executes segmentation and targeting strategies using data insights to support portfolio strategies and risk management.

Skills

Python

SQL

Spark

Tableau

PowerBI

Airflow

Snowflake

BigQuery

Redshift

Jira

Confluence

Azure

AWS

Kafka

Kinesis

Adobe Experience Platform

Salesforce Marketing Cloud

Google Ads

GitHub Copilot

Education

Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field

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