Job Description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, New Jersey Department of Children and Families, is seeking the following. Apply via Dice today! GOVERNMENT REPRESENTATIVE 1 SENIOR DATA PLATFORM ENGINEER (Posting #186-26) SALARY: $120,000 - $150,000 NEW JERSEY DEPARTMENT OF CHILDREN AND FAMILIES (DCF) The Department of Children and Families (DCF), Office of Data Management and Reporting, is seeking a qualified individual to fill the Government Representative 1 - Senior Data Platform Engineer position located in Trenton. This position may be eligible to work remotely for up to two days in a calendar week. Job Description The Senior Data Platform Engineer reports to the Assistant Director in the Data Platform Unit of the Office of Data Management and Reporting. The Senior Data Platform Engineer designs, builds, and operates cloud native data pipelines, storage, compute, and serving layers. Applies expertise in distributed processing, orchestration, and cloud engineering to deliver scalable, high quality data products and services. This role is hands-on, code oriented, and production focused, capable of deep-diving into performance, reliability, and cost optimization while ensuring consistency, security, and data integrity across the platform. Responsibilities include Data Engineering Design, develop, and optimize data pipelines that extract, process, and deliver data from diverse structured and unstructured sources. Apply distributed computing frameworks (e.g., Spark) for large-scale transformation and processing operations, ensuring performance, reliability, and scalability. Build and maintain batch, streaming, API, and CDC ingestion patterns. Integrate data from databases, data warehouses, APIs, and external systems while ensuring data consistency and integrity. Apply data cleansing, enrichment, aggregation, and filtering techniques as part of transformation workflows. Tune and optimize data pipelines by identifying performance bottlenecks and applying techniques such as efficient partitioning, indexing, and caching. Cloud Platform Engineering & Infrastructure Automation Contribute to the strategic direction for implementation of InfrastructureasCode (Terraform/Bicep/CloudFormation) to provision, manage, and secure cloud resources. Build robust CI/CD pipelines to automate deployment of data pipelines, models, and transformations. Recommend cloud security best practices including RBAC/ABAC, key management, secrets management, encryption, network controls, and data access patterns. Monitor and tune cloud resource utilization for both cost efficiency and performance. Observability, Reliability & Production Operations Implement platform observability using logs, metrics, traces, dashboards, and endtoend lineage. Configure runtime orchestration and workflow management (Airflow, ADF, Databricks Jobs, Step Functions, etc.). Provide oncall support for production systems; lead incident response, triage, and root-cause analysis. Establish and maintain SLOs for latency, data freshness, reliability, and resource efficiency. Data Quality, Lineage & Governance Integration Implement automated data validation, quality checks, and integrity rules within pipelines. Ensure lineage is captured and integrated with enterprise metadata/catalog platforms. Work closely with the Data Governance team to apply definitions, steward rules, and classification policies. Help enforce data consistency and quality standards across all ingestion and transformation workflows. Collaboration, Leadership & Reuse Collaborate with analytics, data governance, MDM, and data product teams to ensure alignment with organizational standards. Mentor junior engineers and contribute to establishing engineering best practices. Develop reusable templates, modules, libraries, and patterns to increase engineering productivity and consistency. Participate actively in release readiness, code review, and change control processes. General Responsibilities Perform additional duties as assigned. EXPERIENCE Minimum Qualifications 5-8+ years in cloud data engineering roles. Strong hands-on proficiency in Python, SQL, Spark, orchestration frameworks, and CI/CD. Experience integrating and validating data from multiple storage systems, APIs, and external systems. Experience with data quality, data validation, and lineage tooling. Hands-on experience with Azure or AWS data services (e.g., ADLS/S3, ADF/Glue, Databricks/EMR). Preferred Qualifications Prior exper