Data Engineer

🔥 0 minutes ago

🇮🇳 India – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 13%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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DysrupIT

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2016

🏢 Enterprise

☁️ SaaS

🔒 Cybersecurity

Enterprise • SaaS • Cybersecurity

DysrupIT is a global cloud services and IT solutions firm that helps organizations adopt cloud technologies and transition to as-a-Service business models. The company provides enterprise cloud, managed services, application engineering, cybersecurity, and data analytics & information management, serving SMBs through multinational enterprises with Microsoft and other cloud platforms. DysrupIT also emphasizes community impact, talent development, and long-term partnerships to deliver secure, scalable, and business-aligned technology outcomes.

📋 Description

• Support and enhance data engineering solutions enabling Financial Crime Risk and/or Legal and Corporate Tech platforms • Design, develop, and maintain scalable, resilient data ingestion, transformation, and reconciliation pipelines • Integrate data from multiple internal and external providers into existing platforms and data stores • Transform and curate raw source data to align with target business and technical data models • Migrate and modernise existing data pipelines as enterprise frameworks, tooling, and standards evolve • Develop and optimise complex SQL transformations and large-scale distributed data processing workloads • Implement data quality controls, validation frameworks, reconciliation processes, and monitoring capabilities • Perform root cause analysis and troubleshoot data and platform issues across development, testing, and production environments • Participate in production support, operational incident management, and on-call support rotations • Improve platform reliability, observability, and operational processes through automation and engineering best practices • Collaborate with data architects, platform engineers, business stakeholders, and delivery teams • Contribute to source control, CI/CD pipelines, automated testing, and release management • Promote engineering excellence through knowledge sharing, continuous improvement, and technical leadership

🎯 Requirements

• Strong hands-on experience developing enterprise-scale data engineering solutions • Advanced SQL development skills with experience processing and analysing large datasets • Strong Python development skills for data processing, automation, and integration • Experience building and maintaining complex ETL and ELT pipelines • Strong understanding of data integration patterns and multi-source data processing • Experience working with structured, semi-structured, and large-volume datasets • Strong understanding of data modelling principles and data access patterns • Experience with AWS services, particularly Amazon S3, Amazon RDS, EKS, EC2, Lambda, and IAM • Experience developing and supporting cloud-based data platforms • Experience working with source control systems and modern software development practices • Strong experience implementing data quality controls and validation frameworks • Experience designing reconciliation processes, control totals, and load assurance mechanisms • Experience troubleshooting production issues and supporting critical business systems • Experience participating in operational support and incident management processes • Experience with CI/CD pipelines and automated deployment practices • Experience working with Agile delivery methodologies • Strong stakeholder engagement and communication skills • Ability to balance delivery outcomes with operational stability and platform resilience • Experience with Apache Spark or distributed data processing frameworks • Experience with Apache Airflow, Argo Workflows, Control-M, or equivalent orchestration technologies • Experience with AWS Glue • Experience using Trino or Presto • Experience with containerised workloads and Kubernetes platforms, preferably AWS EKS • Experience modernising or migrating enterprise data pipelines to new ingestion, orchestration, or cloud-based platforms • Experience with OpenSearch / Elasticsearch platforms • Experience working within banking, financial services, or regulated environments • Exposure to Financial Crime Risk technologies and business processes • Exposure to Actimize, ActOne, Quantexa, or similar financial crime platforms

🏖️ Benefits

• Government-mandated benefits plus supplemental HMO coverage • Collaborative and professional work environment • Career growth opportunities within a growing technology organization • Hybrid/Remote work arrangement (where applicable) • Training and support to grow careers