Sprouts.ai - Data Engineer
3 weeks ago
Job Summary :We are looking for an experienced Data Engineer to design, build, and maintain scalable data pipelines and processing systems that power our modern data platform. The ideal candidate will have hands-on expertise in distributed data processing, data lake/lakehouse systems, and workflow orchestration using modern tools such as Spark, PySpark, Apache Iceberg, Apache Hudi, and Apache Airflow.This role will be central in enabling reliable data ingestion, transformation, and governance-ready pipelines to support analytics, AI, and operational use cases across the organization.Key Responsibilities :- Build and maintain scalable ETL/ELT pipelines for batch and streaming data using PySpark and Airflow.- Develop and optimize data ingestion workflows from multiple structured and unstructured data sources.- Implement data lake and lakehouse solutions using Spark with Apache Iceberg, Hudi, or Delta Lake.- Ensure data quality, reliability, and integrity through validation, profiling, and monitoring frameworks and automations using AI.- Support database migration efforts and cross-system data reconciliation.- Collaborate with data scientists, analysts, and platform engineers to enable analytics and ML use cases.- Contribute to data governance practices, including schema evolution, versioned data catalogs (e.g., Nessie), and metadata management.- Troubleshoot and optimize data jobs for performance and cost efficiency.Required Skills & Qualifications :- 6- 10 years of experience in data engineering with strong exposure to big data platforms.- Hands-on experience with PySpark for distributed data processing.- Solid understanding of modern table formats (Apache Iceberg, Hudi, Delta) and versioned data catalogs.- Experience with Apache Airflow (or equivalent) for workflow orchestration.- Strong SQL skills with experience in data modeling and performance tuning.- Exposure to cloud data platforms (AWS, GCP, Azure) and managed services.- Experience with handling large-scale datasets (TBs-100s of TBs).- Understanding of DevOps practices for CI/CD of data pipelines.Nice to Have :- Experience in streaming data frameworks (Kafka, Flink, Spark Streaming).- Knowledge of Sales, Marketing, or CRM domains (Accounts, Contacts data).- Exposure to Elasticsearch, PostgreSQL, or Vector databases.Why Join Us :- Work on cutting-edge open-source data technologies at scale- Grow your expertise in lakehouse, streaming, and AI-ready data architectures.- Contribute to building a governance-ready, modern data platform from the ground up using AI- Collaborate in a fast-paced, innovation-driven culture. (ref:hirist.tech)
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