Director- Data Analytics

Anaptyss; Dadri; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Anaptyss in India seeks a senior data engineering/architecture leader to orchestrate delivery across data lakes and warehouses, and to manage client portfolios while driving analytics initiatives.

You will work with SQL, Python, ETL/ELT tools, and cloud platforms (Azure, AWS, GCP), shaping governance, data models, and enterprise standards. This role requires strong stakeholder communication and a track record of large transformations. BFSI domain knowledge is a plus.

Qualifications

• 14+ years in data engineering, architecture, and analytics with delivery leadership.
• Hands-on across SQL, Python, ETL/ELT, and cloud data platforms (Azure/AWS/GCP).
• Deep data architecture: data lake/warehouse/lakehouse and governance tooling.
• Strong BI background with Power BI, Tableau or Qlik for self-service analytics.
• Experience managing multi-client engagements with governance and executive relationships.
• Proven track record leading large data transformations end-to-end.
• Pre-sales/solutioning: proposals, staffing, and delivery models.
• Excellent stakeholder communication; credible with C-level and technical teams.
• Experience building and scaling data teams; BFSI domain knowledge preferred.

Responsibilities

• Lead data transformation programs end-to-end from strategy to adoption.
• Manage multi-client portfolios with delivery governance.
• Drive pre-sales and solutioning activities for opportunities.
• Define data architectures and governance standards across engagements.
• Collaborate with C-level executives and technical teams to align data strategy.

Skills

Data engineering

Data architecture

Analytics

SQL

Python

ETL/ELT

Cloud data platforms

Azure

AWS/GCP

Data governance

Stakeholder management

Leadership

Education

Bachelor's/Master's in CS/IS/Engineering

MBA a plus

Cloud certifications (Azure/AWS/GCP, TOGAF)

DAMA/CDMP

Tools

Alteryx

Informatica

Azure Data Factory

dbt

Collibra

Purview

Alation

Snowflake

Databricks

Synapse

Redshift

BigQuery

Power BI

Tableau

Qlik

Job description

• 14+ years of experience in data engineering, architecture, and analytics, including substantial experience owning delivery and/or account leadership.
• Proven hands‑on expertise across the full data stack: SQL, Python, ETL/ELT (Alteryx, Informatica, Azure Data Factory, dbt), and cloud data platforms (Azure, AWS, or GCP - Snowflake, Databricks, Synapse, Redshift, BigQuery).
• Deep architectural experience - data lake/warehouse/lakehouse design, enterprise/common data models (CDM), and data governance & catalog tooling (Collibra, Purview, Alation).
• Strong analytics/BI background - Power BI, Tableau, Qlik - and experience enabling self‑service and advanced analytics/AI-ML use cases.
• Demonstrated experience managing multiple client accounts or a portfolio of engagements simultaneously, including account growth, delivery governance, and executive relationship management.
• Track record leading large data transformation programs end‑to‑end - from strategy and roadmap through architecture, build, and adoption.
• Strong pre‑sales/solutioning capability - proposals, RFP responses, staffing plans, and commercial/delivery models.
• Excellent stakeholder management and communication skills - equally credible with C‑level executives and hands‑on technical teams.
• Demonstrated people leadership - building, mentoring, and scaling multi‑disciplinary data teams across engagements.
• BFSI domain knowledge preferred - regulatory/risk reporting, core banking data, and compliance frameworks (BCBS 239, Basel, CCAR).

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Data/Information Systems, Engineering, or a related field; MBA a plus.
• Cloud or architecture certifications (Azure/AWS/GCP, TOGAF) and/or data management certification (DAMA/CDMP).
• Prior experience in a consulting, systems‑integrator, or professional‑services environment managing a multi‑client portfolio.
• Exposure to GenAI/LLM‑driven analytics strategy and its application within regulated industries.