Data Platform Engineer (Data 360)

Coastal•Indianapolis, IN

19h•Hybrid

About The Position

We are looking for a Data Platform Engineer to help us support our continued growth. The Data Platform Engineer is responsible for building, implementing, and maintaining technical solutions, ensuring they align with best practice solutions based on client needs. Working closely with Data Architects, they provide technical execution and development support within Salesforce.com and other SaaS applications to support business and product strategies, with a heavy emphasis on maximizing the Salesforce Data 360 (D360) ecosystem. A Data Platform Engineer participates in discovery sessions to understand client processes and challenges, translating documented solution designs into functional technical requirements and production-ready implementations. They provide collaborative execution and clear communication to project and client team members in order to build a foundation as a trusted technical partner. This position will require a weekly onsite presence at our client's location in Indianapolis, IN.

Requirements

3+ years of experience in data engineering, technical consulting, or database development for cloud data platforms with multiple enterprise workstreams.
Strong working knowledge of the data cloud architecture, including data models (DMOS, DSOs), identity resolution, data spaces, calculated insights, and activation targets.
Familiarity and alignment with modern data architecture methods, including lakehouse architecture, zero-copy data sharing, and real-time data activation.
Hands-on experience with enterprise database technology, cloud data warehouses (e.g., Snowflake, Databricks), ETL/ELT tools, data engineering pipelines, and data science principles.
Excellent verbal and presentation abilities, capable of effectively communicating technical engineering concepts and data updates to stakeholders and team members.
Strong proficiency with data-centric programming languages (such as SQL and Python) as well as Salesforce application development components (Apex, Flow, LWCs, MuleSoft).
Solid understanding of enterprise architecture patterns, API management, and real-time data streaming technologies (e.g., Kafka, Amazon Kinesis).
Practical experience with data modeling methodologies (such as Kimball dimensional modeling, Star/Snowflake schemas, or Medallion Bronze/Silver/Gold structures) and mapping them into a canonical Customer 360 model.
Must have full-time permanent US work authorization.

Nice To Haves

Bachelor’s Degree preferred, or equivalent experience.
Salesforce Certified Data Cloud Consultant or Accredited Professional designations.
Hands-on experience with core Salesforce CRM technology like Sales Cloud, Service Cloud, or Industry Clouds (e.g., Financial Services Cloud, Health Cloud).
Hands-on experience deploying AI/ML solutions like Salesforce Einstein, AWS Sagemaker, or Google Vertex AI, alongside a solid understanding of Generative AI patterns (e.g., Retrieval-Augmented Generation / RAG).
Experience designing data architectures on cloud platforms like Amazon Web Services, Microsoft Azure, or Google Cloud Platform.
Hands-on expertise with analytics and visualization tools like Tableau, CRM Analytics, PowerBI, or Looker.
Open to travel based on client and business demands.

Responsibilities

Implement and maintain data structures that align with business needs, leveraging Salesforce Data 360 (D360) capabilities for unified profile management, data democratization, and real-time activation.
Build and deploy data solutions that bridge enterprise cloud data platforms (Data Lakes/Warehouses) with the Salesforce ecosystem to address specific business needs, such as Business Intelligence (BI), ETL/ELT, and AI/ML initiatives.
Execute the migration, ingestion, and mapping of customer data from legacy systems and siloed databases into the Salesforce D360 platform.
Configure and maintain data accessibility, data privacy, granular security controls, and compliance with relevant regulations (e.g., GDPR, CCPA) and industry standards within the customer data ecosystem.
Develop, deploy, and maintain real-time streaming and batch data pipelines for ingesting, transforming, and loading high-volume enterprise data into Salesforce D360 from various cloud sources and APIs.
Build and support scalable data models and metadata architectures within Salesforce D360, implementing identity resolution rules, reconciliation rules, and unified data graphs as designed.
Monitor, troubleshoot, and optimize query performance, calculated insights, identity resolution runs, and data transformation processes within the Salesforce D360 and underlying lakehouse environments.
Collaborate actively with key stakeholders—including business users, data engineers, data scientists, and CRM IT teams—to understand technical specifications and deliver unified data solutions.
Help evaluate, test, and integrate appropriate tools, connectors, and zero-copy/Zero-Data-Movement technologies for seamless data integration, transformation, and activation within the Salesforce D360 ecosystem.
Provide development-level support, code reviews, and best-practice engineering guidance to data engineering and CRM development teams.

Benefits

Flexible working hours with an emphasis on a life-work balance (in that order!)
Remote flexible work
Unlimited Paid Time Off (RTO)
401K with Company Match
Medical, Vision, & Dental coverage
Competitive quarterly bonus opportunities
Continuing education and certification reimbursements, specifically within the Salesforce and Snowflake ecosystems
Frequent team and culture activities, virtual & in-person, including Lunch and Learns, Happy Hours, team-building events
Monthly All-Hands calls to bring the company together
Open-door leadership policy with access to mentorship and guidance
Opportunities for accelerated growth, networking, and career guidance and support