data engineer

We are looking marketing profile 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.