Senior Tech Lead - Data Engineering & Infrastructure - 10+ years

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Roles & Responsibilities:

• Design and manage scalable data architectures that meet business needs and performance requirements.
• Lead the implementation of data storage solutions, such as data warehouses and data lakes, across hybrid and cloud-based environments (AWS, Azure, or GCP).
• Develop and enforce data governance, quality, and security standards to protect sensitive data and ensure compliance.
• Monitor and troubleshoot data infrastructure and pipeline issues to ensure high availability and reliability.
• Architect / Design, Develop & Support multiple Data Engineering projects with heterogeneous data sources, produce / consume data to / from messaging queues like Kafka, push / pull data to / from REST API’s.
• Support & enhance in-house build Data Integration Framework, Data Replication Framework, Data Profiling & Reconciliation Framework. Support, Enhance & Lead Data Engineering Initiatives, Infrastructure & Architecture.
• Engage / establish best standard practices with third party data providers.
• Translate complex technical subjects into terms that can be understood by both technical and non-technical audiences. Providing direction and guidance to a team of 2 or more - solving problems and resolving conflicts.

Position Requirements:

• 7+ years of experience using Data Integration Tools - Pentaho, Talend or any other ETL / ELT tools.
• 7+ years of experience using traditional databases like Postgres, MSSQL, Oracle
• 4+ years of experience using MPP databases like Vertica, Google BigQuery, Amazon Redshift
• 3+ years of experience in creating Entity-Relationship & Dimensional Data Model.
• 2+ years of experience in Scheduler / Orchestration Tools Like Control-M, Autosys, Airflow, JAMS
• 2+ years of experience in leading a team of 2 or more
• 2+ years of proficiency in at least one programming language, such as Python or Java.
• 2+ years of proficiency in familiarity with cloud-based data storage and processing services, big data technologies (e.g., Spark, Hadoop), and containerization (e.g., Docker, Kubernetes).
• Experience with scripting languages like Shell
• Demonstrated experience with cloud infrastructure services (e.g., AWS, Azure, GCP).
• Strong implementation experience with ETL / ELT Strategies - determining heavy lifting of data using Push Down Or Push Up methods.
• Strong infrastructure architecture/administration knowledge on ELT / ETL Tools - Memory Management, Resource Management, User / Role Management, Performance improvement.
• Strong implementation or working experience in any Code Versioning Tools Strong communication and documentation skills.
• Experience in collaborating with multiple business units like Finance, Marketing, Sales Experience of working in Agile Delivery Model.

Desirable:

• Experience in Data Visualization Tools like Tableau, Pentaho BA Tools.
• Experience on the Hadoop ecosystem - Programmed or worked with key data components such as HIVE, Spark and Sqoop moving and processing terabyte level of data.
• Digital Marketing / Web analytics or Business Intelligence a plus.
• Understanding of Ad stack and data (Ad Servers, DSM, Programmatic, DMP, etc). Knowledge of scripting languages such as Perl or Python.
• Experience in the Linux environment is preferred but not mandatory.