Senior Data Engineer

• Data & Analytical Solutions

  • Designs and delivers scalable data products using standard cloud and data engineering architectures.
  • Owns technical decisions (batch vs. streaming, Lakehouse vs. warehouse) and ensures solutions meet reliability, security, governance, latency, and cost requirements.
  • Reviews designs and contributes reusable components, templates, and standards.

   

  Data Pipelines

  • Builds and operates end‑to‑end batch and streaming pipelines.
  • Implements transformations using SQL/dbt and PySpark as needed.
  • Integrates real‑time or event‑driven ingestion using Kafka.
  • Orchestrates workflows with Airflow; establishes SLAs/SLOs and CI/CD‑based deployments.

   

  Data Systems & Architecture

  • Optimizes data architectures for performance, scalability, and cost.
  • Applies best practices for Iceberg table design, incremental processing, and query optimization across Hive, Impala, Snowflake, and RDBMS.
  • Diagnoses systemic issues and drives remediation with platform teams.

   

  Data Infrastructure (AWS)

  • Leads technical readiness across dev/test/prod environments.
  • Works hands‑on with AWS services including S3, Glue, Lambda, IAM, and SageMaker.
  • Partners with governance and platform teams on access control, tagging, and operational support.

   

  Data Modeling & Formats

  • Leads modeling across RAW, CURATED, and SERVING layers.
  • Applies dimensional or normalized models for correctness, performance, and usability.
  • Implements efficient formats (Parquet + Iceberg) with clear schema evolution strategies.

   

  DevOps & CI/CD

  • Designs and improves Git‑based CI/CD pipelines and infrastructure‑as‑code using Terraform.
  • Ensures quality gates, auditability, and compliance with governance requirements.

   

  Stakeholder & Engineering Leadership

  • Partners with product, analytics, and platform teams to align on requirements, data contracts, and SLAs.
  • Communicates complex technical topics clearly and leads technical discussions.
  • Coaches engineers and raises engineering standards through reviews and documentation.

   

  AI‑First & Product Mindset

  • Uses GenAI‑assisted development responsibly to accelerate delivery.
  • Builds products, not just pipelines, focusing on usability, adoption, reliability, and lifecycle ownership.
  • Designs systems end‑to‑end and continuously optimizes cost‑performance trade‑offs using metrics.

   

Qualifications

• 8+ years of total experience with 6+ years of  Data Engineering experience.
• Strong expertise in AWS‑based data engineering and scalable cloud architectures
• Proven experience building end‑to‑end batch and streaming pipelines, including Kafka
• Advanced proficiency in SQL, Hive, Impala, and PostgreSQL / RDBMS
• Strong programming skills in Python and PySpark
• Hands‑on experience with AWS Glue, Lambda, S3, IAM, and SageMaker
• Experience with Snowflake and modern data warehousing
• Expertise in CI/CD, Terraform, and DevOps practices
• Proficiency in Airflow for workflow orchestration
• Experience with Power BI for data visualization and reporting
  • Strong foundation in data modeling, performance optimization, and large‑scale data systems