Job Purpose and Impact

The Senior Data Engineer designs, builds, and operates scalable, reliable data products and platforms that power analytics, reporting, and downstream applications. This role owns endtoend delivery of batch and streaming data pipelines on a modern AWSbased cloud data platform, applying strong engineering patterns to ensure performance, security, observability, and cost efficiency.
With minimal supervision, the role partners closely with product, analytics, and platform teams to translate business requirements into robust technical solutions across a Lakehouse (Iceberg) and approved warehousing platforms (e.g., Snowflake). The Senior Data Engineer also mentors other engineers, drives code quality, and raises the engineering bar across the organization.

Key Accountabilities

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 endtoend batch and streaming pipelines.
Implements transformations using SQL/dbt and PySpark as needed.
Integrates realtime or eventdriven ingestion using Kafka.
Orchestrates workflows with Airflow; establishes SLAs/SLOs and CI/CDbased 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 handson 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 Gitbased CI/CD pipelines and infrastructureascode 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.

AIFirst & Product Mindset

Uses GenAIassisted development responsibly to accelerate delivery.
Builds products, not just pipelines, focusing on usability, adoption, reliability, and lifecycle ownership.
Designs systems endtoend and continuously optimizes costperformance tradeoffs using metrics.

Qualifications

8+ years of total experience with 6+ years of Data Engineering experience.
Strong expertise in AWSbased data engineering and scalable cloud architectures
Proven experience building endtoend batch and streaming pipelines, including Kafka
Advanced proficiency in SQL, Hive, Impala, and PostgreSQL / RDBMS
Strong programming skills in Python and PySpark
Handson 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 largescale data systems

Senior Data Engineer