Associate Director, Data Ingestion Delivery

Johnson Controls, Inc.; Milwaukee (WI); Presencial; USD 150.000 - 210.000; Jornada completa

Descripción de la vacante

Johnson Controls, Inc. is seeking a Data Ingestion Leader to own the strategy and architecture for enterprise data ingestion. You will lead engineering, establish reusable patterns, and drive secure, reliable onboarding of diverse data sources into the enterprise data platform.

You will guide data quality, governance, and observability while partnering with Enterprise Architecture and platform leadership to ensure scalable, compliant ingestion capabilities across domains.

Formación

• Bachelor’s degree or equivalent professional experience in a related discipline.
• At least 10 years in data engineering or related areas; 5+ years leading large programs.
• Experience designing and operating enterprise-scale data ingestion architectures; strong CI/CD/DataOps background.

Responsabilidades

• Own and execute the enterprise data ingestion strategy and roadmap.
• Architect and operate a reusable ingestion framework with scalable, secure data pipelines.
• Establish onboarding standards, data quality, lineage, and governance.
• Lead and develop a high-performing ingestion engineering team.
• Collaborate with architecture, platform leadership, and domain data delivery leaders.
• Ensure reliability, observability, and incident response for ingestion pipelines.

Conocimientos

Data engineering

Data ingestion

Team leadership

CI/CD

DevOps

DataOps

APIs and API management

ETL/ELT

Cloud data platforms

Observability

Educación

Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Management, or related discipline

Herramientas

Snowflake

Microsoft Azure

Azure Data Factory

Databricks

Kafka

SQL

Python

Descripción del empleo

About Us

Johnson Controls, a global leader in thermal management, mission-critical building systems, energy efficiency, and decarbonization, helps customers use energy more productively, reduce carbon emissions, and operate with the precision and resilience required in rapidly expanding industries such as data centers, healthcare, pharmaceuticals, advanced manufacturing, and higher education. For more than 140 years, Johnson Controls has delivered performance where it really matters. Backed by advanced technology, lifecycle services and an industry-leading field organization, we elevate customer performance, turn goals into real-world results and help move society forward.

What we offer

• Competitive salary and bonus opportunity
• Comprehensive benefits package
• Paid vacation, holidays, and sick time
• Extensive product and on-the-job training
• Encouraging and collaborative team environment
• Dedication to safety through our Zero Harm policy
• Opportunities to lead an enterprise data capability with broad organizational impact

What you will do

The Data Ingestion Leader is accountable for the strategy, architecture, engineering, delivery, and operational reliability of enterprise data ingestion capabilities. This role owns the enterprise-wide ingestion layer, providing a standardized, scalable, secure, and reusable capability for acquiring structured, semi-structured, and unstructured data from enterprise source systems into the enterprise data platform.

You will establish reusable ingestion patterns that make onboarding a new data source primarily a configuration-driven activity rather than a custom engineering project. You will ensure that data arrives reliably and securely while meeting agreed freshness and availability service-level agreements.

How you will do it

Enterprise Data Ingestion Strategy

• Own the enterprise roadmap and strategy for data ingestion.
• Establish common ingestion patterns for batch, streaming, API, file, database, software-as-a-service, and event-based sources.
• Drive standardization and reuse across business domains and source-system technologies.
• Eliminate unnecessary point-to-point integrations and duplicate ingestion solutions.
• Partner with Enterprise Architecture and platform leadership to align ingestion patterns with enterprise data architecture principles.

Ingestion Framework and Engineering

• Build and operate a reusable, metadata- and configuration-driven ingestion framework that accelerates source onboarding and minimizes custom development.
• Establish engineering standards for schema detection and evolution, incremental and change data capture processing, restart and recovery, idempotency, data validation, reconciliation, observability, logging, error handling, metadata capture, security, and encryption.
• Develop reusable connectors and templates for strategic enterprise source platforms.
• Apply consistent engineering practices to improve scalability, maintainability, security, and operational support.

Source Onboarding and Intake

• Establish a documented intake and prioritization process for new ingestion requests.
• Partner with source-system owners to understand availability, interfaces, refresh requirements, data volumes, dependencies, and business criticality.
• Define onboarding standards and acceptance criteria that must be met before production deployment.
• Maintain an enterprise source inventory that identifies the owner, refresh cadence, criticality, and sensitivity classification of each feed.

Reliability, Service Levels, and Observability

• Define and publish data freshness and availability service-level agreements for downstream teams.
• Implement proactive ingestion monitoring and alerting so failures are identified before they affect downstream consumers.
• Own pipeline reliability, incident response, root-cause analysis, and corrective-action delivery.
• Establish dashboards covering pipeline health, freshness, latency, throughput, failures, and service-level attainment.
• Apply DataOps and site reliability engineering practices to continuously improve ingestion reliability.

Data Quality and Governance at Ingestion

• Implement automated data validation as information enters the platform.
• Ensure source-to-Bronze reconciliation and ingestion completeness.
• Automate the capture of technical metadata and lineage wherever possible.
• Ensure ingestion pipelines follow applicable security, privacy, retention, and data governance standards.
• Partner with Data Governance and Data Stewards on classification, ownership, sensitivity, and lifecycle requirements.
• Ensure Bronze-layer data complies with applicable enterprise controls.

Lifecycle and Technical Debt Management

• Own the execution of ingestion-related retention and lifecycle requirements.
• Monitor unused datasets and manage their archival or removal according to defined policies.
• Identify and retire legacy, manual, and unsupported ingestion mechanisms.
• Maintain a modernization roadmap for high-risk or unsupported ingestion interfaces.

Team Leadership

• Lead and develop a high-performing team of ingestion engineers and technical leads.
• Establish clear engineering standards, code-review practices, and technical ownership.
• Build team capabilities across cloud data engineering, APIs, streaming, change data capture, DevOps, DataOps, and automation.
• Establish engineering capacity planning and delivery accountability.
• Foster a culture of automation, reuse, engineering excellence, continuous improvement, and operational ownership.

Stakeholder and Delivery Management

• Partner closely with source-system owners, Enterprise Architecture, Data Platform Strategy and Standards, Data Governance, Data Operations, and domain data delivery leaders.
• Collaborate with Cybersecurity, Privacy, Infrastructure, Cloud, business, and analytics teams to deliver secure and reliable ingestion capabilities.
• Manage stakeholder expectations, dependencies, risks, priorities, and delivery commitments across enterprise initiatives.
• Support vendor management and technology decisions related to enterprise ingestion capabilities.

What we look for

Required

• Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Management, or a related discipline, or equivalent professional experience.
• At least 10 years of experience in data engineering, data integration, data platforms, or adjacent disciplines.
• At least five years of experience leading technical teams, major platforms, programs, or engineering capabilities.
• Demonstrated experience designing and operating enterprise-scale data ingestion architectures.
• Strong understanding of ETL and ELT, APIs, change data capture, event and streaming architectures, data lakes and lakehouses, data warehousing, metadata, lineage, data quality, observability, and cloud data platforms.
• Experience applying CI/CD, DevOps, and DataOps practices to production data pipelines.
• Demonstrated enterprise architecture thinking, strategic planning, engineering excellence, and operational ownership.
• Strong people leadership, stakeholder management, problem-solving, change leadership, risk management, and continuous-improvement capabilities.

Preferred

• Experience with Snowflake and Microsoft Azure.
• Experience with Azure Data Factory or Fabric Data Factory.
• Experience with Databricks.
• Experience with Kafka or other event-streaming platforms.
• Experience with APIs and API management platforms.
• Experience with change data capture technologies.
• Experience integrating data from SAP, Oracle, and Salesforce.
• Proficiency with SQL and Python.
• Experience with Git-based CI/CD practices.
• Experience with enterprise data observability and monitoring platforms.
• Experience managing technology vendors and strategic delivery partners.