Technical Lead, Scalable Data Solutions
2 days ago
This is a leadership role in our Data Platform team, focusing on architecting and implementing scalable data solutions using AWS services. The successful candidate will be responsible for leading the development of data pipelines, structuring and evolving data into optimized formats, and driving data productization for downstream services.
Key Responsibilities:
- Design and implement scalable data lake architectures for both streaming and batch workloads, leveraging AWS-native services.
- Lead the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark.
- Structure and evolve data into optimized formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services.
- Drive data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases.
- Define and track service level agreements and service level objectives for critical data pipelines, ensuring high availability and data accuracy in a regulated environment.
- Collaborate with InfoSec, SRE, and Data Governance teams to enforce data security, lineage tracking, access control, and compliance.
- Utilize Generative AI tools to enhance developer productivity, including auto-generating test harnesses, schema documentation, transformation scaffolds, and performance insights.
Requirements:
- At least 7 years of experience in data engineering.
- Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum.
- Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs.
- Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation.
- Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale.
- Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions.
- Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments.
- Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains.
- Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders.
What We Offer:
We offer a competitive compensation package, opportunities for professional growth, and a collaborative work environment that fosters innovation and creativity.
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