Senior Data Engineer

iSEO Ranker; Karachi Division; Hybrid; PKR 33,296,000 - 49,945,000; Full time

Job summary

Sarovar Inc, in collaboration with iSEO Ranker, is hiring a Senior Data Engineer to design, build, and scale a cloud-based data platform for Wealth Management and Financial Services in the USA. You will own data pipelines, data infrastructure, and production run operations, working with UI and API teams to deliver reliable, scalable data capabilities.

The role emphasizes Airflow, Python, SQL, and DevOps on Azure, AKS, and related CI/CD workflows, with opportunities to apply Spark-based workloads

Qualifications

• 4+ years of hands-on data engineering, pipeline engineering, or backend data platform development.
• Experience with Apache Airflow or similar workflow orchestration for production data pipelines.
• Strong Python and SQL development experience, including data-processing technologies like pandas.
• Experience writing efficient SQL queries and building staging, merge, reconciliation, and performance-tuned workflows on SQL Server or similar systems.
• Experience building reliable ingestion pipelines for files, APIs, and third-party data feeds.
• DevOps/operational experience on Azure or other public clouds, including storage services and containerized deployments.

Responsibilities

• Design, build, and maintain data pipelines and platform components with engineering leadership.
• Develop and optimize Airflow DAGs and Python-based workflows, plus SQL-driven ingestion and load processes.
• Support daily production run operations, incident triage, reruns, and root-cause analysis.
• Improve data quality controls, observability, and reliability across pipelines.
• Onboard new accounts, data sources, and workflow requirements safely and efficiently.
• Lead deployment, configuration, and operational processes for Airflow and data infra on Azure/AKS.

Skills

Python

SQL

Airflow

Data pipelines

Collaboration with eng teams

Tools

Azure

AKS

Kubernetes

Databricks / Spark

CI/CD

Delta Lake

Job description

Sarovar Inc, IN Collaboration with iSEO Ranker, provides software development and solutions design services to the FinTech and Financial Services industry in the USA. We are hiring a Senior Data Engineer to support the continued growth of our cloud-based data platform. The company provides excellent compensation, mentoring, skills development, and opportunities to work on emerging cloud and data technologies.

The Senior Data Engineer will be a key member of the engineering team responsible for the design, development, operation, and scaling of the platform's data pipelines and data infrastructure. This role offers the opportunity to apply deep technical experience while helping build a highly scalable and robust cloud-based data platform for Wealth Management and Financial Services use cases. The engineer will work alongside the broader team, including UI and API engineers, but will primarily focus on data pipelines, DataOps, production run operations, reporting and scaling the platform as more accounts, workflows, and datasets are onboarded.

Responsibilities

• Research, design, build, and maintain data pipelines and related platform components in consultation with engineering leadership and the broader engineering team.
• Develop and optimize Airflow DAGs, Python-based data-processing workflows, and SQL-driven ingestion, staging, reconciliation, and load processes.
• Support daily production run operations for business-critical data workflows, including incident triage, reruns, root-cause analysis, and operational issue resolution.
• Implement and improve data quality controls, validation checks, exception handling, observability, and operational reliability across the pipeline estate.
• Work with engineering, business, and external stakeholders to onboard new accounts, data sources, and workflow requirements safely and efficiently.
• Strong deployment, configuration, and operational processes for Airflow and related data infrastructure in Azure, AKS, and associated CI/CD workflows.
• Participate in or lead on-call and run-ops responsibilities for the data platform.
• Identify performance, scalability, and architecture bottlenecks and recommend or implement solutions that improve throughput, resilience, and maintainability.
• Help define the next phase of the data platform, including opportunities for distributed processing, Spark-based workloads, data lakes, lakehouse patterns, and other scale-oriented architecture improvements appropriate for Wealth Management and Financial Services workloads.
• Build strong and positive working relationships with client teams, internal developers, and other vendor teams supporting the broader platform.

Desired Skills and Experience

• 4+ years of hands-on experience in data engineering, pipeline engineering, or backend data platform development.
• Strong experience with Apache Airflow or a similar workflow orchestration platform for building and operating production data pipelines.
• Strong hands-on development experience in Python, SQL, and related data-processing technologies such as pandas.
• Experience writing efficient SQL queries and implementing staging, merge, reconciliation, and performance-tuned data workflows on SQL Server or similar relational database platforms.
• Experience building reliable ingestion pipelines for files, APIs, and third-party data feeds in production environments.
• Experience supporting production data systems, including incident response, reruns, operational debugging, and root-cause analysis.
• DevOps and operational experience on Azure or other major public cloud providers, including storage services such as Blob Storage or ADLS, containerized deployments, and cloud-based operational tooling.
• Experience with Kubernetes, AKS, Helm, CI/CD pipelines, and operational ownership of containerized data platforms is strongly preferred.
• Experience designing or implementing scalable data architectures using Spark, PySpark, Databricks, Synapse, data lakes, Delta Lake, or similar distributed-processing and lakehouse technologies is strongly preferred.
• Experience evolving existing pipelines toward more scalable architectures as data volumes, account counts, and operational complexity increase.
• Strong understanding of data quality, idempotency, failure recovery, monitoring, alerting, and production reliability for data platforms.
• Experience in financial services, wealth management, portfolio data, risk data, account data, or other correctness-sensitive business domains is preferred.
• Experience working collaboratively with software engineers across adjacent systems such as APIs, downstream applications, QA workflows, and shared platform services.

Note: Its a Hybrid Job (3 days office, 2 days work-from-home)