Senior Data Engineer

We are looking for a Senior Data Engineer / Technical Lead to architect and lead enterprise-scale data engineering solutions for a leading technology and telecommunications organization. The ideal candidate will have strong expertise in Snowflake, Databricks, Python/PySpark, SQL, Azure, streaming, CI/CD, data quality, and enterprise data platforms, along with strong finance and revenue data experience. Candidate Requirements • Senior-level experience in Data Engineering / Technical Leadership. • Strong experience with Snowflake and Databricks. • Advanced Python/PySpark and SQL skills. • Strong Azure/cloud data platform experience. • Experience with ETL/ELT, batch, incremental, CDC, and streaming pipelines. • Experience with Kafka / Event Hub, Spark Structured Streaming, Airflow, and ADF. • Strong understanding of CI/CD, DevOps, data quality, security, and governance. • Experience with finance/revenue data, billing, GL, reconciliation, and financial reporting. • FAANG experience mandatory; Tier 1 product-based companies may be considered. Required Skills • Data Engineering & Technical Leadership • Snowflake • Databricks / PySpark • Python / Advanced SQL • Azure / ADLS Gen2 • Azure Data Factory / Airflow • Kafka / Azure Event Hub • Spark Structured Streaming • dbt • Delta Lake / Unity Catalog • ETL / ELT / CDC • CI/CD / Azure DevOps / GitHub Actions • Terraform / Bicep • Data Quality & Observability • Data Modeling • Data Security & Governance • Finance & Revenue Data Required Qualifications • Proven experience designing and leading enterprise-scale data pipelines. • Strong hands-on experience with Snowflake, Databricks, Python/PySpark, and SQL. • Experience with scalable batch, incremental, CDC, and real-time data processing. • Strong Azure experience with services such as ADLS Gen2, Event Hub, ADF, and Key Vault. • Experience with Airflow/dbt and modern data engineering frameworks. • Strong knowledge of data quality, testing, observability, monitoring, and data governance. • Experience with CI/CD, infrastructure-as-code, and deployment automation. • Understanding of RBAC, PII/CPNI, data lineage, auditability, and secure pipeline design. • Experience with enterprise data models, SCD Type 1/2, partitioning, clustering, and performance optimization. • Strong knowledge of billing, revenue, GL, reconciliation, revenue recognition, and financial reporting. • Strong communication, analytical, problem-solving, and technical leadership skills. • Bachelor's degree in Computer Science, Information Systems, Engineering, or related field preferred. Preferred Qualifications • Experience with FAANG companies – Facebook/Meta, Amazon, Apple, Netflix, or Google. • Experience with Tier 1 product-based companies. • Advanced experience with Snowflake Snowpipe, Streams, Tasks, and optimization. • Strong Databricks, Delta Live Tables, Unity Catalog, and PySpark experience. • Experience with dbt, Great Expectations, and data observability frameworks. • Experience with real-time finance/revenue data processing. • Experience with Terraform/Bicep and cloud infrastructure automation. • Experience leading teams, mentoring engineers, and driving engineering best practices. Key Responsibilities • Architect and lead enterprise-scale ETL/ELT pipelines for high-volume finance and revenue data. • Design scalable batch, incremental, CDC, event-driven, and streaming solutions. • Lead architecture and adoption of Snowflake and Databricks. • Establish best practices for PySpark, SQL, dbt, Airflow, ADF, and cloud data platforms. • Architect real-time solutions using Kafka, Event Hub, and Spark Structured Streaming. • Drive data quality, testing, observability, SLA monitoring, and data governance. • Define CI/CD, DevOps, code quality, and release management standards. • Implement enterprise security controls including RBAC, PII/CPNI compliance, secrets management, lineage, and auditability. • Support data modeling, performance optimization, partitioning, and clustering. • Provide technical leadership for HLD/LLD, design reviews, code reviews, testing, and releases. • Partner with architects, developers, product managers, analysts, and business stakeholders. • Lead incident reviews, defect RCA, troubleshooting, and continuous improvement. • Mentor team members, provide technical guidance, and drive engineering excellence. • Communicate complex technical solutions clearly to technical and non-technical stakeholders. ABOUT BRICKRED SYSTEMS BrickRed Systems is a technology consulting and workforce solutions company focused on helping organizations improve business efficiency and technology performance. The company provides services across technology consulting, data services, AI, cloud solutions, engineering, business intelligence, quality assurance, and IT operations. BrickRed also provides contingent workforce, hybrid talent, and managed workforce solutions, supporting organizations with skilled professionals across onshore, nearshore, and offshore delivery models. With expertise across data management, analytics, cloud solutions, engineering, and digital transformation, BrickRed Systems helps clients solve complex technology and workforce challenges while enabling scalable and efficient business operations.