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.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data architecturedata engineeringSQL query designETLELTdata pipeline developmentdata quality validationdata processing systemsbig data environmentsdata warehouse architecture

Soft Skills

analytical skillstroubleshootingproblem-solvingcommunicationdocumentationmentoringleadershipcollaboration