Senior Databrick Engineer /Lead
Peoplentech Llc
Alexandria, VA, United States
8 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Compensation
$156,000
Working hours
Regular working hours
Job source
Tech stack
Unity 3d
Artificial Intelligence
Airflow
Amazon Web Services
Amazon S3
Apache HTTP Server
Big Data
Databases
Continuous Integration
Directed Acyclic Graph (Directed Graphs)
Data Architecture
Information Engineering
+31 more
Data Governance
Extract Transform Load (ETL)
Data Migration
Data Security
DevOps
Github
Apache Hive
Identity and Access Management
Python (Programming Language)
Machine Learning
Meta-Data Management
Performance Tuning
Data Streaming
Electronic Medical Records
Generative AI
Data Strategy
Data Lakes
Pyspark
Infrastructure Automation Frameworks
Real Time Data
Apache Nifi
Data Management
Machine Learning Operations
Stream Processing
Data Pipelines
Serverless Computing
Cisco
Amazon Elastic Mapreduce (EMR)
Jenkins
Amazon Redshift
Databricks
Job description
- Lead enterprise-scale data platform modernization initiatives, driving migration from AWS EMR, Apache NiFi, and legacy ETL frameworks to the Databricks Lakehouse Platform.
- Architect and implement scalable Lakehouse solutions using Databricks, Delta Lake, Unity Catalog, and Databricks Workflows.
- Design and govern end-to-end data pipelines for batch, streaming, CDC, and real-time data integration workloads.
- Provide architecture leadership for large-scale AWS-based data ecosystems leveraging S3, IAM, Redshift, Glue Catalog, Airflow, and Databricks.
- Develop enterprise data architecture standards covering data modelling, metadata management, lineage, governance, security, and compliance.
- Drive adoption of Databricks best practices including Delta Live Tables (DLT), Auto Loader, Unity Catalog, Serverless Compute, Lakehouse Federation, and advanced optimization techniques.
- Lead replatforming and migration programmes involving PySpark applications, Airflow DAGs, EMR workloads, Redshift integrations, and NiFi pipelines.
- Partner closely with business stakeholders, enterprise architects, product owners, and data science teams to define technology roadmaps and target architectures.
- Establish governance frameworks using Unity Catalog, data quality controls, observability, monitoring, and operational excellence practices
- Provide technical leadership, mentoring, architecture reviews, design governance, and solution sign-offs across multiple delivery teams.
- Lead architecture workshops, executive presentations, solution assessments, and technology evaluations.
Mandatory Technical Skills
- Databricks Lakehouse Platform
- Delta Lake, Delta Live Tables (DLT)
- Unity Catalog
- Databricks Workflows
- Auto Loader
- PySpark, Spark SQL, Python
- AWS (S3, IAM, Glue, Redshift, EMR, Lambda)
- Apache Airflow
- CDC & Data Migration Frameworks
- Data Governance & Security
- CI/CD, GitHub, Jenkins
JD:
- Lead enterprise-scale Databricks Lakehouse Architecture design and implementation on AWS.
- Drive large-scale data platform modernisation and cloud transformation initiatives.
- Architect scalable Medallion Architecture (Bronze, Silver, Gold) data platforms.
- Lead migration of legacy EMR, NiFi, Redshift, and ETL workloads to Databricks.
- Design high-performance batch and real-time data processing solutions.
- Build robust ingestion frameworks using Auto Loader, Delta Lake, and Structured Streaming.
- Define enterprise data governance and security standards using Unity Catalog.
- Architect metadata-driven and reusable PySpark-based ETL/ELT frameworks.
- Establish best practices for performance tuning, scalability, and cost optimisation.
- Design and implement data quality, lineage, and observability frameworks.
- Drive adoption of CI/CD, DevOps, Infrastructure as Code, and automation practices.
- Collaborate with business, analytics, and engineering teams to define target-state architectures.
- Conduct architecture reviews and provide technical leadership across multiple projects.
- Mentor architects and senior engineers on Databricks and AWS best practices.
- Design secure and scalable solutions leveraging AWS services (S3, Glue, Athena, Lambda, IAM, Redshift).
- Implement and govern enterprise-wide data access, compliance, and security controls.
- Evaluate and adopt latest Databricks capabilities such as DLT, Lakehouse Federation, Serverless, and MLflow.
- Enable AI/ML, Generative AI, and advanced analytics use cases on the Lakehouse platform.
- Create architecture roadmaps, migration strategies, standards, and governance frameworks.
- Act as the primary technical advisor for customer leadership on data strategy and platform evolution.
Requirements
Engineering, Database Extract Transform and Load (ETL), Electronic Medical Records, Amazon Web Services (AWS), Apache, Cisco Unity, Centers for Disease Control and Prevention (CDC), Data Management, Leadership, Ecosystems, Need resources who have strong, demonstrable data engineering experience with a proven track record of designing and implementing production-grade solutions on the Databricks Lakehouse platform
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