Analytics Engineer · 6+ Years in IT · Cloud Data Pipelines & Modeling
I build reliable data pipelines and warehouse models that turn raw source systems into trusted, analytics-ready data — using SQL, Python, and Snowflake across banking, government, defense, aviation, pharma, healthcare, telecom, and retail.
About Me
With over six years in IT, I work as an Analytics Engineer helping organizations — including Fortune 500 companies — design the pipelines, data models, and warehouse structures that turn raw source systems into clean, trusted, analytics-ready data.
As a US citizen with deep experience on projects involving sensitive government, defense, and financial data, I bring a grounded understanding of US data protection, privacy, and federal compliance requirements — including fair lending regulations and HMDA reporting.
Work Authorization
US Citizen — no sponsorship needed, eligible for federal and defense projects.
Availability
Open to remote, hybrid, or on-site roles. Willing to relocate anywhere in the US and travel up to 100% if required.
Domain Focus
Currently specialized in banking and financial services — credit risk pipelines, fair lending data models, and regulatory reporting datasets.
Working Style
Agile practitioner comfortable owning the full pipeline lifecycle — from source ingestion to modeled, tested, documented datasets ready for BI.
Technical Expertise
My toolkit spans the full analytics engineering lifecycle — from raw source ingestion and transformation through data modeling, warehousing, and analytics-ready delivery.
Informatica, pipeline design, data masking with Delphix, OpenRefine for cleansing. End-to-end pipelines across multi-source environments.
SQL, PL/SQL — Oracle, SQL Server, IBM Db2, MySQL, PostgreSQL. Dimensional modeling, complex queries, stored procedures, performance tuning.
Amazon Redshift, Google BigQuery, Azure Synapse Analytics, and Snowflake — warehouse architecture and cloud-native analytics at scale.
Pandas, NumPy, Scikit-learn. Data pipeline scripting, validation, statistical analysis, predictive modeling, and LLM integrations.
Power BI (DAX, row-level security, paginated reports), Tableau — modeling clean semantic layers for downstream dashboards.
Advanced Excel — pivot tables, Power Query, formula-driven workbooks, and audit-ready regulatory reporting models.
Industry Experience
I've delivered data solutions across a wide range of sectors. This cross-industry experience means I recognize data patterns and business problems others might miss — and I bring that perspective to every engagement.
Services
I work with organizations that want more from their data than one-off reports. My engagements are focused on the underlying pipelines and models — the infrastructure that makes accurate, reusable analytics possible.
Scalable data pipelines from source to warehouse — cleansed, validated, and documented for ongoing operations.
Dimensional models, star schemas, and SQL-based transformation layers built for performance and reuse.
Snowflake, Redshift, and Synapse implementations — schema design, performance tuning, and cost-aware scaling.
Automated checks, reconciliation logic, and documentation that keep pipelines trustworthy as they scale.
Clean, well-modeled datasets and semantic layers that make Power BI and Tableau dashboards fast and reliable.
HMDA and fair lending data pipelines, QC frameworks, and compliance-ready datasets across Illinois and national data.
Contact
Ready to discuss a role, a project, or a data challenge? Reach out directly — I respond promptly.
biplab@biplabadhikary.com