Data Platform EngineerLakehouse Architecture
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Job Location:
Monthly Salary:
Posted on:
10 hours ago
Vacancies:
1 Vacancy
Job Summary
We are seeking an experienced Data Platform Engineer to design and implement a cloud-based data lakehouse platform that ingests engineering and security tool data transforms it through multiple layers and serves it to both analytics dashboards and AI agents.
Experience:
- 8 years in data engineering roles with at least 2 years building lakehouse architectures (Bronze/Silver/Gold or equivalent medallion patterns)
- Proven track record delivering production-grade data platforms
- Experience with graph databases (Neo4j Amazon Neptune TigerGraph) for relationship modeling
- Hands-on with stream processing (Kafka Flink Spark Streaming Kinesis)
Technical Skills (Core):
- Cloud Platforms: Deep expertise in AWS (S3/Blob RDS/SQL Database managed Kafka serverless compute)
- SQL & Data Modeling: Expert-level SQL dimensional modeling SCD2 normalization vs. denormalization trade-offs
- Transformation Tools: dbt Databricks SQL Dataform or custom SQL/Python frameworks
- Programming: Python or Scala for data processing scripting and automation
- Orchestration: Airflow Prefect Dagster Step Functions or Azure Data Factory
- IaC: Terraform CloudFormation Pulumi or ARM templates
Technical Skills (Preferred):
- Search: OpenSearch Elasticsearch or Solr for text indexing and retrieval
- Graph: Neo4j Cypher SPARQL or Gremlin for graph queries; experience with graph ETL
- Data Quality: Great Expectations dbt tests or custom validation frameworks
- Real-time: Flink Spark Streaming or serverless event processing (Lambda Cloud Functions)
- Monitoring: Grafana Datadog or CloudWatch for data pipeline observability
Professional Skills:
- Communication: Explain technical trade-offs (cost performance complexity) to non-technical stakeholders
- Problem-Solving: Debug data quality issues optimize slow queries resolve schema conflicts
- Collaboration: Work with data scientists DevOps engineers and compliance teams
- Autonomy: Manage ambiguity; propose solutions when requirements are incomplete
Key Skills
- Apache Hive
- S3
- Hadoop
- Redshift
- Spark
- AWS
- Apache Pig
- NoSQL
- Big Data
- Data Warehouse
- Kafka
- Scala
About Company
At Infotree, meeting your career needs is a top priority. Client satisfaction is largely dependent on the resources we can provide, and we take pride in our delivery. We have a supportive team in place to give quality people a chance to grow and challenge themselves in their roles whi ... View more
