Technical Skills:
1. Basic Qualifications
a. Education: Bachelor’s or master's in computer science, Applied Mathematics, Engineering, or a related quantitative field.
b. Experience: Minimum of 3-5 years of professional "hands-on-keyboard" coding experience in a collaborative, team-based environment. Ability to trouble shoot (SQL) and basic scripting experience.
c. Languages: Professional proficiency in Python or Java.
d. Methodology: Deep familiarity with the full Software Development Life Cycle (SDLC) and CI/CD best practices & K8s deployment experience.
2. Core Data Engineering Competencies: Candidates must demonstrate a sophisticated understanding of the following modeling concepts to ensure data correctness during reconciliation:
a. Temporal Data Modeling: Managing state changes over time (e.g., SCD Type 2).
b. Schema Management: Expertise in Schema Evolution (Ref: Iceberg Apache) and enforcement strategies.
c. Performance Optimization: Advanced knowledge of data partitioning and clustering.
d. Architectural Theory: Balancing Normalization vs. Denormalization and the strategic use of Natural vs. Surrogate Keys.
3. Technical Stack Requirements: While candidates are not expected to be experts in every tool, the collective team must cover the following technologies:
Extraction & Logic: Kafka, ANSI SQL, FTP, Apache Spark
Data Formats: JSON, Avro, Parquet
Platforms: Hadoop (HDFS/Hive), Snowflake, Apache Iceberg, Sybase IQ