Build a Smarter Data Foundation.

We design and manage end-to-end data pipelines that connect, transform, and activate your business-critical data—from marketing to operations to executive insights.

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Data Engineering Services

What Is Data Engineering?

Data engineering is the foundation of modern digital intelligence. It ensures that raw, fragmented data from dozens of platforms is cleaned, unified, and ready for reporting, automation, and AI. Without it, analytics fail—and automation breaks. At On Beat Digital, we don't just pipe data—we architect performance.

Core Data Engineering Services

Data Integration & Ingestion

  • Connecting APIs from platforms like Eloqua, Salesforce, GA4, Adobe, HubSpot, Shopify, Stripe, and more
  • Batch, streaming, and event-driven ingestion
  • Webhook & form-based data capture
  • File ingestion (CSV, XLSX, JSON, SFTP, cloud buckets)

Data Cleaning & Transformation (ETL/ELT)

  • Field normalization and type coercion
  • Deduplication and null handling
  • Lookup table joins and reference data mapping
  • Flattening nested structures (JSON/XML to tables)
  • Row- and column-level filtering and logic
  • Semantic layer creation for self-service BI

Data Modeling & Warehousing

  • Star & snowflake schema design
  • Data lake architecture (S3, Redshift Spectrum, Azure Blob)
  • Cloud warehouse configuration: Redshift, BigQuery, Snowflake, PostgreSQL
  • Dimensional modeling and slowly changing dimensions (SCD)
  • Partitioning and clustering strategies

Data Pipeline Automation

  • Python-based ETL scripts and scheduled jobs
  • Workflow orchestration using tools like Apache Airflow or AWS Step Functions
  • dbt (data build tool) deployment and testing
  • Versioned pipeline deployment (CI/CD for data)

Reporting-Ready Structures

  • Custom views for Power BI, Tableau, or Looker
  • Pre-aggregated summary tables
  • KPI-centric data marts
  • Funnel, cohort, and time-series formats
  • Business-friendly column naming

Cloud Architecture & Optimization

  • AWS (S3, RDS, Glue, Lambda, Redshift) configuration and optimization
  • GCP or Azure support on request
  • IAM permissions and secure data zones
  • Cost-optimized data retention and archival

Built to Support...

Marketing & Attribution
  • Eloqua → Redshift pipelines
  • Campaign metadata enrichment
  • Multi-touch attribution modeling
Sales & CRM
  • Salesforce sync and object mapping
  • Deal progression tracking
  • Territory and rep-level performance
Web & Behavior
  • GA4, Clarity, Hotjar event pipelines
  • Session stitching
  • Behavior-based cohort modeling
Finance & Ops
  • eCommerce transactions
  • Stripe/QuickBooks ingestion
  • LTV modeling, margin & churn analytics

AI & Predictive Layer Optional Add-On

  • ML-ready table generation for churn, LTV, and scoring models
  • Integration with tools like ODIN for weekly data-driven strategy
  • Content and customer scoring pipelines
  • Embedded analytics for marketing automation systems

AI-powered data insights

Enterprise-grade security

Security & Compliance

  • GDPR, CCPA, HIPAA-conscious design
  • Row-level security enforcement
  • Access logging and audit trails
  • Automated PII detection and tagging
  • Data masking, hashing, and encryption workflows

Example Deliverables

Snowflake Schema Diagram

Visual data warehouse structure

dbt Project with Lineage

YAML-documented transformation flows

Power BI Dataset View

Business-ready reporting structure

API Dataflow Map

Eloqua → S3 → Redshift → Tableau

JSON Schema

Marketing event payload structure

Data Engineering Success Stories

Real data pipelines driving business intelligence

Multi-Source Data Integration

Unified 12 siloed data sources combining Eloqua, Salesforce, and GA4 data, accelerating time-to-insight by 87% and eliminating manual exports.

Data Integration ETL Pipeline Business Intelligence
Read Case Study

Comcast Revenue Forecasting

Advanced data pipeline with predictive analytics model for revenue forecasting using time-series analysis and machine learning algorithms.

Data Pipeline Predictive Analytics Revenue Forecasting
Read Case Study

User System Revamp

Complete data architecture overhaul with modern ETL processes, improved data quality, and streamlined analytics workflows.

Data Architecture System Migration ETL Optimization
Read Case Study

Why On Beat Digital?

We speak both analyst and engineer
Decade of experience with martech data
AI-enhanced pipeline recommendations via ODIN
Zero-bloat architecture (no tech debt traps)
Hands-on deployment support + stakeholder education

Data engineering expertise

Frequently Asked Questions

Ours are lean, flexible, and built to support real-world use cases like attribution, automation, and campaign-level reporting—not just warehouse dumps.

Yes. We integrate Eloqua, HubSpot, Marketo, Salesforce, and custom platforms with full field and event mapping.

Yes. We can host, monitor, and evolve your pipelines with monthly service plans—or hand it off with training and full documentation.

Absolutely. From schema design to infrastructure to dashboard-ready views.

We implement column-level encryption, masking, and access logging. We can also build workflows for consent flagging and data retention rules.

Let's build your data backbone.

Whether you need a quick funnel report or a full-scale data warehouse, On Beat Digital can architect, automate, and activate your data.

Book a Data Engineering Strategy Call