Syedor Rahman

Provide a boutique style personalised data management consulting service which provides the following services

• Deriving a data strategy which aligns with your business objectives and goals

• Data management architecture & security

• Data quality management & governance

• Data processing & modelling

• Advanced data analytics & visualisations

• Machine Learning and AI Solutions – Architecture, model selection, finetuning & evaluation, API Endpoints, Vector Knowledgebase, Agentic AI

Involved in initial C level data initiative roadmap requirement gathering, engage with delivery leads and Business SMEs to derive SOWs for delivery, lead on ETL patterns discovery and strategy, lead on testing approaches, risk and issues resolution and post production support.

Some success stories

Client – Worldwide Vertiport operator that enable passenger/cargo eVTOL operators to take off/land

Project - Derive a greenfield data strategy to process and govern data from multiple sources.

Architecture must be cloud based, deployed via DEVOPS IAC CI/CD pipelines, 4 9’s SLA for Uptime, transparent for regulatory requirements and horizontally scalable for future sites across the GCC.

Client – Utilities provider in the emirate of Dubai

Project – Review current data strategy and provide 2nd opinion on technology and governance choices to address risk mitigation for such a substantial financial investment. Conduct workshops, provide a detailed summary which outline alignment to priorities and future projects, alternative technology choices with pros/cons and a transparent independent evaluation.

Client – B2B events entertainment solution platform

Project – Introduction of data integration between core systems to keep data synched as close to real time. Provide a matchmaker algorithm API for use in core platforms to eradicate manual processing.

Automate critical business processes using cognitive AI solutions to reduce admin time/costs and increase customer/supplier satisfaction.

Derive a data strategy that aligns with a group strategic merger of several brands to drive a common approach into customer journey, group level visibility, improve accounting processes and cost savings.

Derive a group level data roadmap that encompasses a new central unified data lakehouse platform, a data governance tool and a common data model that will address the gaps across the Insights, data science and BI group reporting

Set up a group wide data engineering function that is responsible for the execution of the initiatives.

Manage a team of data engineers that span Europe, MENA and Asia.

Contribute to Software Delivery Life Cycle process that improves our processes/data quality and efficiency of our data pipelines.

Lead on a cloud first event driven approach to all group wide ETL/ELT processes.

Set up a data integration function that encompasses data quality checks at each REST level which benefits multiple areas with one point of intervention leading to improved data quality for ML/AI models, accounting integration into SAP4 HANA and business intelligence insights that have minimal gaps in data completeness.

Work closely with Business Unit SMEs to identify data gaps in data analytics/decision models and drive initiatives to onboard 3rd party data/improvement of internal data quality issues to fill these gaps.

Lead on ITDATASECOPS initiatives to promote secure movement, resting and processing of PI data.

Investigate an initiative for AI powered Code review to improve code standards.

Derive a proposal for improved pre-processing of common data sets to help optimise downstream AI LLM’s.

Investigate and propose AI tools and models that could drive efficiencies and AI understanding within the business.

Working with high volume real time streaming data pipelines that are fed from MT4 and MT5 Platforms

Trading activity data exposure spanned FX. Commodities, indices and equities, copy trading, PAMM, Affiliates and IB’s

Reporting to the CIO to drive the strategy for a group merger of shared data functions across 3 financial product organisations.

Manage a department of 40 data engineers/technical data analysts/analytical platform professionals residing across both onshore/offshore teams.

Leading the right balance of onshore/offshore data engineer resource for changing project portfolio demand and staff turnover risk (scale up/down resource as required).

Work closely with my counterparts across the group to deliver an operating model that will phase the initiatives of the migration strategy which did not impact the delivery of important regulatory projects.

Work with enterprise architects and act as the data engineering expert for target data tech stack gap analysis and tool selection.

Lead on a cloud first approach to all group wide ETL/ELT processes.

Own current risks on risk register, drive initiatives and gain funding to introduce controls to mitigate.

Work closely with Business Unit SMEs to identify data gaps in data analytics/decision models and drive initiatives to onboard 3rd party data/improvement of internal data quality issues to fill these gaps.

Work closely with Enterprise Architect and Data Architects to achieve a metadata driven framework for ingestion and transformation of data using Azure Data Factory/Databricks/Snowpipe/Snowflake.

Work with cloud engineering to create CI/CD release process using Terraform and ARM templates.

Work with scrum masters and delivery leads on multiple boards on Azure DEVOPS to roll up into a portfolio of deliverable projects. Managing capacity and allocation of sprints.

Architect the framework for a collective Azure ADF/ADL/DATABRICKS/SYNAPSE solution together with parametrised pipelines that form the code standards.

Lead on a monitoring solution for data pipelines and automated alerts using Grafana and Splunk

Propose cloud OPEX cost reductions by comparing existing and newly available Azure data products.