5 days ago
Responsibilities
- Lead the architecture, design, deployment, and management of scalable, high-throughput Big Data systems.
- Build data systems supporting AI infrastructure, including vector, NoSQL, and document databases.
- Develop end-to-end ETL/ELT pipelines, API services, and data ingestion frameworks.
- Design storage and processing layers for analytics, including data lakes, data warehouses, distributed file systems, and real-time streaming architectures.
- Build feature-rich context pipelines using batch and streaming processing patterns.
- Optimize distributed queries and data transformations for performance and low latency.
- Implement data quality, integrity, reliability, and governance frameworks across data assets.
- Collaborate with analytics, product, and platform teams on data models for customer metrics, hierarchies, and relationships.
- Evaluate modern data-stack tools, distributed computing frameworks, and database technologies.
- Lead technical projects and mentor engineering teams.
Requirements
- Extensive hands-on data engineering experience delivering in complex data environments.
- Deep practical knowledge of vector databases, NoSQL databases, and document stores used in AI and machine learning infrastructure.
- Experience building, scaling, and shipping large-scale data platforms in production.
- Deep experience with distributed data processing frameworks such as Apache Spark, Flink, or Hadoop.
- Strong expertise with message brokers and event streaming platforms such as Apache Kafka or Kinesis.
- Extensive experience with data pipeline lifecycle development and workflow orchestration tools such as Apache Airflow or Dagster.
- Hands-on expertise with cloud data warehouses such as Snowflake, BigQuery, or Redshift.
- Experience with data lake architectures and technologies such as Databricks, Delta Lake, or Apache Iceberg.
- Advanced SQL skills and proficiency in Python.
- Strong background in software development practices including testing, code review, CI/CD, and Infrastructure as Code.
- Experience with cloud-native infrastructure such as AWS, GCP, or Azure is desirable.
- Experience implementing data observability, monitoring, and alerting frameworks at scale is desirable.
- Familiarity with Anaplan or similar enterprise planning platforms is desirable.
Benefits
- The role is open to candidates located in the Eastern or Central time zones.
- Employees within commuting distance of an Anaplan office are expected to work onsite two days per week under the hybrid work model.
- Anaplan provides reasonable accommodations for individuals with disabilities and supports an inclusive, diverse workplace.
Tech Stack
Amazon RedshiftApache AirflowApache FlinkApache HadoopApache KafkaApache SparkAWSAzureDatabricksGoogle BigQueryGoogle Cloud PlatformPythonSnowflakeSQL
Categories
Data Engineering
About Anaplan
Anaplan is a leading AI-driven scenario planning and analysis platform designed to optimize decision-making in today’s complex business environment so that enterprises can outpace their competition and the market. By building connections and collaboration across organizational silos, our platform intelligently surfaces key insights — so businesses can make the right decisions, right now. More than 2,500 global brands plan with Anaplan.