Data Engineer

Position: Data Engineer

Duration: 3 Months with extension

Location: Montgomery AL (Onsite from day 1)

Job Description:

In summary: A Data Quality Engineer strong data analyst with deep technical skills in SQL Purview Data Pipelines and Data Modeling plus experience in cloud data environments automated testing and collaboration with analytics and engineering teams. Ensures data is not only clean but also ready to support advanced analytics and AI applications

Responsibilities

Data Quality Engineer & Analytics Skills

• Data Profiling & Cleansing: Analyze data to identify anomalies duplicates outliers and missing values; apply cleansing techniques to improve data integrity.
• SQL Proficiency: Write complex queries to validate data accuracy perform transformations and generate reports. (SSIS - ETLELT)
• Python & Other Languages: Python is widely used for automation data validation and integration with analytics pipelines; SQL is essential for querying and reporting.
• Data Modeling & Warehousing: Understand ETL/ELT processes data warehouse/lake/lakehouse architectures and data modeling principles.
• Cloud & Modern Data Stack: Experience with cloud platforms (AWS GCP Azure) modern data warehouses (Snowflake BigQuery) and tools like Spark Kafka/Kinesis Hadoop or S3.
• Data Testing & Observability: Design and deploy automated data testing at scale; use observability platforms for real-time monitoring.

Analytics & Data Science Skills

• Data Quality Standards & Metrics: Define and enforce data quality benchmarks; measure completeness accuracy timeliness and consistency.
• Root Cause Analysis: Identify why data issues occur (ETL bugs user input errors system failures) and implement fixes.
• Collaboration with Data Scientists: Work with ML/data science teams to ensure training data is clean and reliable.
• Statistical & Trend Analysis: Interpret patterns in large datasets to inform quality improvements.

Soft & Communication Skills

• Stakeholder Engagement: Gather requirements from business engineering and analytics teams; advocate for data quality across the organization.
• Problem-Solving & Attention to Detail: Spot and resolve data issues efficiently; maintain high precision in validation.
• Documentation: Record quality issues processes and improvements for transparency and compliance.

Tools & Platforms

• Query & Analysis: SQL Python Spark Kafka/Kinesis Hadoop S3.
• Data Quality Tools: Data profiling tools (MS Purview) validation scripts observability platforms.
• Collaboration: Jira Snowflake or other data governance platforms.

Required skills

• Strong experience working in low or immature data environments establishing data quality processes from scratch (8-10 Years)
• Advanced SQL expertise for complex querying data validation and transformation (8-10 Years)
  Hands-on experience with ETL/ELT pipelines (e.g. SSIS or similar tools) (8-10 Years)
• Proficiency in Python for data automation validation and pipeline integration (5-8 Years)
• Experience with data profiling and cleansing (anomalies duplicates outliers missing values) (8-10 Years)
  Solid understanding of data modeling and data warehouse/lake/lakehouse architectures (8-10 Years)
• Experience implementing data quality frameworks and metrics (accuracy completeness timeliness consistency) (8-10 Years)
  Experience with cloud data platforms (AWS Azure or GCP) and modern data warehouses (e.g. Snowflake BigQuery) (5-8 Years)

Required Tools & Platforms: (8-10 Years) Query & Analysis: SQL Python Spark Kafka/Kinesis Hadoop S3. Data Quality Tools: Data profiling tools (MS Purview) validation scripts observability platforms. Collaboration: Jira Snowflake or other data governance platforms

Preferred skills

• Knowledge of DAMA-DMBoK DCAM MDM concepts and governance frameworks. (8-10 Years)
• Experience with Microsoft Purview Fabric MS Power BI and Key Vault (5-8 Years)
• Familiarity with AI/ML data readiness and feature-store-aligned data structuring. (5-8 Years)
  Cloud data engineering exposure (Azure Databricks GCP). (5-8 Years)

Masters degree preferred.

Certification :- DAMA CDMP (Associate/Practitioner) EDM Council DCAM ASQ Data Quality Credential Collibra Data Steward Certification Certified Data Steward (eLearningCurve) Cloud/AI certifications (Azure Databricks Google)