Data Architect leading data architecture and design for LifeByte's technology ecosystem. Collaborating with multiple teams to ensure robust data governance, compliance, and innovative strategies.
About the role
- Senior Data Engineer at Deep Sync leading data architecture and pipeline development. Designing scalable data solutions for AI-powered data solutions with a focus on data quality and governance.
Responsibilities
- Design and evolve scalable, secure, and high-performance data architectures supporting large-volume, high-velocity data.
- Establish data engineering standards, design patterns, and best practices.
- Evaluate and recommend tools, frameworks, and technologies for data processing and storage.
- Lead the design, implementation, and maintenance of robust, scalable data pipelines.
- Ensure data quality, validation, lineage, and observability throughout the pipeline lifecycle.
- Implement fault-tolerant and highly available data processing systems.
- Architect and oversee ETL/ELT frameworks transforming raw data into analytical and operational datasets.
- Integrate data from diverse sources including relational databases, APIs, third-party providers, and streaming platforms.
- Collaborate cross-functionally with product managers, analysts, ML engineers, and software teams.
Requirements
- 5–8+ years of experience in data engineering or related fields.
- 5+ years of advanced SQL query design, performance tuning, and optimization.
- 5+ years of experience in data warehouse architecture, implementation, and support.
- 5+ years of hands-on experience with ETL/ELT design, development, testing, and troubleshooting.
- Proven experience working with large-scale or “big data” environments.
- Knowledge & Skills Expert-level proficiency in SQL design and implementation.
- Strong experience with Relational Data Warehouse Systems and Data Warehouse Management Systems.
- Deep understanding of indexing, partitioning, denormalization, and query optimization techniques.
- Experience building and optimizing large-scale data pipelines and distributed architectures.
- Proficiency in one or more programming languages such as Python, Java, or C#.
- Experience with cloud data platforms and modern data tooling (e.g., AWS, Azure, GCP, Spark, Airflow, Snowflake, Databricks, etc.) is highly desirable.
- Strong analytical, troubleshooting, and problem-solving skills.
- Excellent communication and documentation abilities.
- Experience mentoring engineers and leading technical initiatives.
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